O Ratsiatosika

E Blanchart

T Razafimbelo

M Razafindrakoto

K Vom Brocke

T-V Cao-Hamadou

J-M Rakotomalala Andriamarosata

A Ramanantsoanirina

J Trap

Affiliations

Does rice breeding affect the ability of plants to interact with earthworms in nutrient-depleted Ferralsols?

Keywords: Agroecology, plant-mutualistic free-living organisms, plant-soil interactions, breeding programme

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Plant breeding programmes mainly focus on crop adaptation to environmental and biotic stresses to increase yields. In the Highlands of Madagascar, breeding was used to develop high yielding and adapted upland rice varieties due to (i) cold climate at the high altitudes [START_REF] Raboin | Upland rice varieties for smallholder farming in the cold conditions in Madagascar's tropical highlands[END_REF], (ii) poor mineral fertility of Ferralsols (Raminoarison et al., 2019), and (iii) blast disease caused by the ascomycete fungus Pyricularia oryzae Cavara [START_REF] Dusserre | Conservation agriculture cropping systems reduce blast disease in upland rice by affecting plant nitrogen nutrition[END_REF]. However, because wild plants have evolved over time with specific soil biota as their plant-mutualistic partners, plant breeding is also a practice that may affect interactions between cultivated plants and soil organisms [START_REF] Barot | Breeding rice cultivars to enhance positive feedbacks between soil and crops? In: Breeding for resilience: a strategy for organic and low-input farming systems?[END_REF][START_REF] Litrico | Diversity in plant breeding: a new conceptual framework[END_REF].

Indeed, by developing genetically homogenous crops with higher yields, resistance to pests and higher tolerance to climatic stresses, plant breeding may have considerable effects on plant-soil interactions [START_REF] Bakker | Harnessing the rhizosphere microbiome through plant breeding and agricultural management[END_REF][START_REF] Mariotte | Plant-soil feedback: bridging natural and agricultural sciences[END_REF]. For instance, the response of crop plants to soil life is known to vary with the presence of bacteria [START_REF] Briones | Influence of different cultivars on populations of ammonia-oxidizing bacteria in the root environment of rice[END_REF][START_REF] Hardoim | Rice root-associated bacteria: insights into community structures across 10 cultivars[END_REF], mycorrhizal fungi [START_REF] Declerck | Mycorrhizal dependency of banana (Musa acuminata, AAA group) cultivar[END_REF][START_REF] Hetrick | Mycorrhizal response in wheat cultivars: relationship to phosphorus[END_REF][START_REF] Vallino | Rice root colonisation by mycorrhizal and endophytic fungi in aerobic soil[END_REF], protists [START_REF] Somasundaram | Functional role of mucilage-border cells: a complex facilitating protozoan effects on plant growth[END_REF], or earthworms [START_REF] Barot | Breeding rice cultivars to enhance positive feedbacks between soil and crops? In: Breeding for resilience: a strategy for organic and low-input farming systems?[END_REF][START_REF] Junaidi | Root traits and root biomass allocation impact how wheat genotypes respond to organic amendments and earthworms[END_REF][START_REF] Noguera | Amplifying the benefits of agroecology by using the right cultivars[END_REF]. To date, plant breeding strategies with mutualistic freeliving soil organisms as direct selection targets are poorly developed [START_REF] Gopal | Microbiome selection could spur next-generation plant breeding strategies[END_REF][START_REF] Wei | Plant breeding goes microbial[END_REF]. Knowing that soil organisms can significantly promote plant functions, this lack of consideration is seen as a significant failure [START_REF] Altieri | The ecological role of biodiversity in agroecosystems[END_REF][START_REF] Barrios | Soil biota, ecosystem services and land productivity[END_REF].

Earthworms present a worldwide-distributed soil biota [START_REF] Phillips | Global distribution of earthworm diversity[END_REF] and are involved in key soil functions (Lavelle, 1997;Lavelle et al., 2006;Jouquet et al., 2006Jouquet et al., , 2008)). They are known to increase plant growth via different mechanisms [START_REF] Brown | How earthworms affect plant growth: burrowing into the mechanisms[END_REF][START_REF] Scheu | Effects of earthworms on plant growth: patterns and perspectives[END_REF]:

(i) increased mineralization of soil organic matter [START_REF] Bernard | Endogeic earthworms shape bacterial functional communities and affect organic matter mineralization in a tropical soil[END_REF][START_REF] Coq | Earthworm activity affects soil aggregation and organic matter dynamics according to the quality and localization of crop residues -An experimental study (Madagascar)[END_REF]; (ii) production of plant growth substances via stimulation of microbial activity [START_REF] Blouin | Chemical communication: An evidence for co-evolution between plants and soil organisms[END_REF];

(iii) control of pests and parasites (Blanchart et al., 2019;[START_REF] Loranger-Merciris | How earthworm activities affect banana plant response to nematodes parasitism?[END_REF]; (iv) stimulation of symbionts [START_REF] Huhta | The role of soil fauna in ecosystems: A historical review[END_REF] and (v) modifications of soil porosity, aggregation and water retention [START_REF] Blanchart | Effects of earthworms on soil structure and physical properties[END_REF]. Breeding modern high-yielding cultivars takes place under high input conditions (i.e., mineral fertilizers and chemical treatment of pests) in soils that can be unfavourable to earthworms [START_REF] Doran | Soil health and sustainability: managing the biotic component of soil quality[END_REF][START_REF] Ponge | The impact of agricultural practices on soil biota: A regional study[END_REF].

Therefore, it is possible that these cultivars have lost some of the plant functional traits involved in interactions with earthworms, which may result in contrasting responses of plants to earthworm presence. For instance, [START_REF] Noguera | Amplifying the benefits of agroecology by using the right cultivars[END_REF] showed that the effects of Pontoscolex corethrurus on rice growth varied significantly for different cultivars and to the presence of biochar. However, the factors e.g., genetic background, agronomic selection criteria and targeted plant traits that determine this variability in plant responses to earthworms remain unidentified.

In the Ferralsols of Madagascar, upland crops face several edaphic constraints. Ferralsols are very infertile with numerous limiting nutrients, especially P but also N, Ca, Mg [START_REF] Raminoarison | Multiple-nutrient limitation of upland rainfed rice in ferralsols: a greenhouse nutrientomission trial[END_REF]. They have very low carbon contents and a low biological activity leading to a very poor productivity of the native vegetation. In the Highlands, the main earthworm species (i.e. P. corethrurus (Rhinodrilidae), Dichogaster bolaui, Dichogaster saliens (Acanthodrilidae), and Amynthas corticis (Megascolecidae)) can deeply modify soil structure and soil C and N cycles and P availability [START_REF] Trap | Effects of the earthworm Pontoscolex corethrurus on rice P nutrition and plant-available soil P in a tropical Ferralsol[END_REF]. This last function is especially important for P-fixing soils such as the Ferralsols.

In the present study, by using a mesocosm greenhouse experimental approach, we aimed to assess the effects of earthworms on the growth and nutrition of six locally widespread upland rice cultivars that are adapted to the nutrient-depleted Ferralsols in Madagascar. We also tested whether agronomic selection criteria or the genetic signals among cultivars may explain the various responses of rice cultivars to earthworm inoculation. For this purpose, the relationships between the response of rice cultivars to earthworm inoculation and agronomic or phylogenetic dissimilarity among the cultivars were assessed.

Materials and methods

Soil sampling

The upper 10 cm layer of a Ferralsol (FAO classification) in a natural grassland was collected from the experimental station of the "Laboratoire des Radio-Isotopes" (LRI) in Lazaina (18°46'55 59° S,47°32'46 3°N,1,274 m altitude,Madagascar) in October 2016 from a 2 m² area. In the laboratory, the soil sample was dried at room temperature for 7 days and was then mixed using a shovel and then by hand to homogenize the sample. Most of the roots and vegetation debris were removed. The soil was then sieved to 2 mm and stored at room temperature in the dark for further analysis of soil properties.

Soil analyses

Total soil organic carbon and nitrogen were measured by dry combustion in a Flash 2000 CHNS analyser (Flash 2000 Series, CHNS/O 122 Analyser Thermo Scientific, IRCOF, France). The Olsen method [START_REF] Olsen | Estimation of available phosphorus in soils by extraction with sodium bicarbonate[END_REF]) was used to determine the plant-available P content.

Total P was evaluated by digestion (4 h at 600°C) with perchloric acid (HClO4) for extraction and by using a spectrophotometer and the colorimetry method (molybdenum blue) to analyse dosage. Cation exchange capacity (CEC), exchangeable K, exchangeable Mg, and exchangeable Ca were analysed using cobaltihexamine extraction and measured using an atomic absorption spectrophotometer (iCE 3000 Series AA spectrometer, Belgium). The exchangeable Al ions were extracted with a 1 N KCl solution and assayed by titrimetry with NaOH. The soil pH in water and in 1 M KCl were measured using a glass electrode pH metre (pH 211 microprocessor pH metre, Hanna Instruments, Romania) with a volume ratio of 1:2.5, and particle sizes were determined with the hydrometer method [START_REF] Okalebo | Laboratory methods of soil and plant analysis: a working manual[END_REF].

The soil had a sandy-clay texture, pH (H2O) of 5.5, total organic C content of 20.8 g kg -1 , total N-content of 1.3 g kg -1 , C:N ratio of 16, total P content of 380 mg kg -1 , Olsen P content of 7.12 mg kg -1 , and exchangeable K, Ca and Mg contents of 30.7, 120.7 and 28.3 mg kg -1 , respectively. The CEC was 1.34 cmol+ kg -1 , and the water-holding capacity was 0.49 g g -1 dry soil.

Biological materials

Individuals of P. corethrurus (Rhinodrilidae) were used in the experiment. This endogeic, geophagous, peregrine species is dominant in all pedo-climatic regions in Madagascar [START_REF] Razafindrakoto | New records of earthworms (Oligochaeta) from Madagascar[END_REF]. It is a 5-8cm in length, weighing 0.7 g in average at the adult stage. This earthworm is able to live in an exceptionally substantial range of soil and climate environments. P. corethrurus individuals were collected near the experimental station in Lazaina and were stored in the same soil before use. Six upland rice (Oryza sativa L.) cultivars commonly used by farmers in the Highlands were studied: "B22", "FOFIFA-161", "FOFIFA-172", "FOFIFA-182", "NERICA-4" and "WAB 880-1-32-1" (Supplementary Table S1). Seeds were provided by the Madagascar National Centre for Applied Research on Rural Development (FOFIFA) and the French Agricultural Research Institute for Development (CIRAD) All cultivars are fully described in the official catalogue of rainfed rice cultivars in Madagascar [START_REF] Raboin | Création variétale pour la riziculture pluviale d'altitude à Madagascar: bilan de 25 années de selection[END_REF][START_REF] Radanielina | The original features of rice (Oryza sativa L.) genetic diversity and the importance of within-variety diversity in the highlands of Madagascar build a strong case for in situ conservation[END_REF]. These rice cultivars cover the narrow current genetic diversity panel that can be found in the Highlands of Madagascar. To test the relationship between the ability of these cultivars to respond to earthworms and their agronomic characteristics, we collected agronomic data for each cultivar from the official catalogue. These agronomic data (e.g., optimal altitude for cropping, maximal grain yield, tolerance to the root parasite Striga asiatica or the disease Pyricularia oryzae, cycle duration, grain weight, length of panicle and cold tolerance) of each cultivar described in the catalogue are the result of several years of field research on the genetic improvement of rainfed rice in the Highlands of Madagascar as part of the plant genetic programme led by CIRAD and FOFIFA (Supplementary Table S1) [START_REF] Raboin | Two-component cultivar mixtures reduce rice blast epidemics in an upland agrosystem[END_REF][START_REF] Raboin | Création variétale pour la riziculture pluviale d'altitude à Madagascar: bilan de 25 années de selection[END_REF][START_REF] Raboin | Upland rice varieties for smallholder farming in the cold conditions in Madagascar's tropical highlands[END_REF][START_REF] Raboin | Upland (aerobic) rice breeding for the harsh environment of the High Plateau of Madagascar, in: Innovation and Partnerships to Realize Africa's Rice Potential[END_REF][START_REF] Radanielina | The original features of rice (Oryza sativa L.) genetic diversity and the importance of within-variety diversity in the highlands of Madagascar build a strong case for in situ conservation[END_REF]. The rice agronomic data from the programme were averaged over 6 years of upland rice cropping under high mineral fertilization levels (e.g., 150 kg ha -1 of N:P:K = 11:22:16 and 80 kg ha -1 of urea) and organic fertilization levels (5 t ha -1 of cattle manure).

Experimental design

The experiment was conducted at the Radio-Isotopes Laboratory (LRI) of the University of Antananarivo (Madagascar). Two treatments were considered: (i) an earthworm treatment including two modalities, i.e., without earthworms (-EW) and with earthworms (+EW) and (ii) a rice cultivar treatment that included six modalities. Each treatment was replicated five times.

Mesocosm setup

The mesocosms consisted of 1 L plastic pots that were previously pierced (2 holes) at the bottom to avoid water accumulation. Each hole was filled with a cotton mesh to facilitate water flow. To prevent earthworms from escaping from the mesocosm, a mosquito net was placed at the bottom of the mesocosms. A total of 60 mesocosms (2 earthworm modalities × 6 rice cultivars × 5 replicates) were filled with 1 kg of sieved dry soil. At the beginning of the experiment, mesocosms were watered with 350 ml of rainwater to mimic field conditions. Three seeds of each rice cultivar were sown. Three adults of P. corethrurus with a well-developed clitellum and similar fresh mass (mean fresh weight of adults ~0.8 g) were introduced into each mesocosm. This earthworm density (~150 individuals per m²) corresponds to field density [START_REF] Rakotomanga | Diversité de la macrofaune des sols cultivés sur les Hautes-Terres de Madagascar[END_REF]. During the experiment, the mesocosms were placed outside under natural weather conditions. The soil moisture content was maintained at 80% water holding capacity by weekly regular weighing. The mesocosm placements were changed every two weeks and used a new randomization. The experiment lasted 8 weeks.

Measurements of earthworm survival rates and rice traits

At the end of the experiment, the soil was gently removed from the mesocosms to check for earthworm presence. All earthworm individuals (adults, juveniles, cocoons) were collected by hand sorting. We calculated the earthworm survival rate based on abundance, expressed as the initial percentage. To evaluate the photosynthetic activity of rice leaves, the photochemical reflectance index (PRI) and normalized difference vegetation index (NDVI) of each rice cultivar were measured using PlantPen PRI 200 & NDVI 300 [START_REF] Gamon | Monitoring seasonal and diurnal changes in photosynthetic pigments with automated PRI and NDVI sensors[END_REF]. Five measurements were randomly performed on the largest leaf in each mesocosm every week and at the end of the experiment. Only the maximum values among the five were considered for data analysis. We also scanned the same largest leaf at the end of the experiment at 600 ppi to obtain the leaf area using the "Easy Leaf Area" software (Department of Plant Sciences, University of California). The final leaf dry matter content (LDMC) was determined after drying the leaves at 65°C for 48 h, and the specific leaf area (SLA) was calculated as the ratio of leaf area to leaf dry mass. Roots were separated from the soil by carefully washing the root system under flowing water to remove soil particles. The shoots and roots were dried at 65°C for 48 h and weighed. Total N contents in shoots and roots were measured by a CHNS/O elemental analyser (Flash 2000 Series, CHNS/O 122 Analysers Thermo Scientific, IRCOF, France). P contents in shoots and roots were determined after digestion of plant tissues with nitric acid 65%. P was measured in the digested solutions by colorimetry. The totals of N and P amounts in rice tissues were calculated by multiplying the N and P contents by biomass. N and P uptake efficiencies (NUE and PUE) were calculated as the ratio of P amounts in shoots by root biomass.

Statistical analyses

Ecological distance

To obtain a statistical distance among cultivars that can be used as the response to earthworm inoculation, we used the Cohen's d effect size [START_REF] Cohen | Statistical power analysis for the behavioral sciences[END_REF]: d = (Mi_+EW -Mi_-EW)/(SDi-pooled) for the "i" cultivar, where M+EW is the mean of the rice trait for the +EW treatment, M-EW is the mean of the rice trait for the -EW treatment and SD-pooled is the pooled standard deviation of the rice trait. The Cohen's d effect size was thus calculated for each rice trait and for each cultivar using the five replications to determine the means and standard deviations (n= 5). We then computed the ecological distance using Cohens' d-values between all pairs of rice cultivars based on the Euclidean distance using the "dist" function from the R package "stats" (Supplementary Table S2).

Phylogenetic distances

We assessed the phylogenetic distance among all pairs from the six cultivars (Supplementary Table S2). The molecular information is stored and managed through a web-based tool, Gigwa-Genotype investigator, for genome-wide analyses [START_REF] Sempéré | Gigwa v2-Extended and improved genotype investigator[END_REF]. In all cases, the complete sequence of the Nipponbare rice cultivar (Os-Nipponbare-Reference-IRGSP-1.0) was used as a reference for alignments. The Tassel GBS pipeline v3.0 [START_REF] Glaubitz | TASSEL-GBS: a high capacity genotyping by sequencing analysis pipeline[END_REF] allowed us to filter the raw data. Data were filtered for minor allele frequencies (MAF ≥ 5%) and missing rates (< 20%). A total of 36,744 Single Nucleotide Polymorphisms (SNPs) were obtained. TASSEL software version 5.0 [START_REF] Bradbury | TASSEL: software for association mapping of complex traits in diverse samples[END_REF] was used to estimate the genetic distance matrix. These analyses considered only 7,338 non-missing loci.

Agronomic distances

We computed the agronomic distance matrix (Supplementary Table S2) by using data collected in previous plant genetic programmes performed in Madagascar (Supplementary Table S1). We used the following agronomic criteria: optimal altitude ranges for cropping (m), maximal grain yield in fertile field situations (t ha -1 ), tolerance to the root parasite Striga asiatica, cycle duration (days), grain weight (g), panicle length (cm) and cold tolerance from spikelet fertility (%). All data were collected from the cultivar catalogue that was created by the rice genetic programme of CIRAD and FOFIFA. The data were available in published studies [START_REF] Raboin | Création variétale pour la riziculture pluviale d'altitude à Madagascar: bilan de 25 années de selection[END_REF][START_REF] Raboin | Upland rice varieties for smallholder farming in the cold conditions in Madagascar's tropical highlands[END_REF][START_REF] Raboin | Upland (aerobic) rice breeding for the harsh environment of the High Plateau of Madagascar, in: Innovation and Partnerships to Realize Africa's Rice Potential[END_REF] or from unpublished technical sources but with free access on the internet (www.dpspad.org/productions2/documents-techniques). The Euclidean distances for all cultivar pairs were calculated with the "dist" function from the R package "stats". We did not weight the different agronomic parameters.

Data analyses

Means and standard deviations (n=5) for each variable were computed for each treatment. The normality of the data was checked using the Shapiro-Wilk test. Data were transformed with the Box-Cox transformation when required. Two-way analyses of variance (ANOVA) were then conducted with the two main factors and their interactions: earthworm inoculation ("EW") including two modalities (absent or present) and rice cultivars covering six modalities. The significance threshold was set to 5%. We also computed the eta-squared (eta²) from ANOVA as a measure of effect size (% of variance explained) [START_REF] Cohen | Eta-squared and partial eta-squared in fixed factor ANOVA designs[END_REF]. We detected the significant differences among the cultivars using the Tukey HSD post hoc test.

The agronomic, phylogenetic and ecological distances among all pairs of cultivars were transformed to fit between 0.1 and 1.0 using a homothetic transformation; Y = 0.1 + ((x -b/(a -b)) × 0.9, where Y is the value of a variable after transformation, x is the distance to transform, a is the maximum distance and b is the minimum distance among the cultivars.

Then, the linear relationships between the ecological, phylogenetic and agronomic distances among cultivars were tested using parametric Pearson's product-moment correlation coefficients at the 5% significance threshold.

Results

Earthworm survival rate

At the end of the experiment, the earthworm survival rate ranged on average from 93% to 107% for all rice cultivar treatments (Supplementary Fig. S1). We found no significant differences (P > 0.05) in the earthworm survival rates among rice cultivars.

Effect of cultivars on rice traits

After eight weeks of growth, all leaf traits, except for NDVI, were significantly different among rice cultivars (Table 1). On average, F161 had the highest leaf area, LDMC and SLA, regardless of earthworm treatments (Table 2). A significant effect for rice cultivars was found for shoot biomass and shoot P and N amounts (Table 1). The highest values for shoot biomass and shoot P and N amounts were found for cultivars B22 and F161, respectively (Table 2).

The lowest values were observed for F172 and N4.

Effect of earthworms on rice traits

The inoculation of P. corethrurus (+EW) had a strong significant effect on rice traits, except for LDMC, SLA, shoot:root ratio and PUE (Table 1). On average, rice cultivars had higher PRI (+57%), NDVI (+34%), shoot biomass (+99%), root biomass (+93%), total biomass (+96%), shoot P amount (+87%), root P amount (82%), total rice P amount (+84%) and shoot N amount (+267%) in the presence of earthworms than in their absence (Table 2).

Interaction effects of earthworms and cultivars on rice traits

We found significant interactive effects of earthworms and rice cultivars on root biomass, shoot:root ratio, and N and P acquisition efficiency (Table 1). Considering the eta² of the different sources of variation from the ANOVA models, we identified eight rice traits that were mostly affected by earthworms (eta² ranged from 49% to 68%), including physiological traits (e.g., SLA, PRI, and NDVI), growth traits (e.g., shoot biomass and total biomass) and nutrition traits (e.g., shoot P amount, total rice P amount and shoot N amount). For instance, in the presence of earthworms, SLA increased by 146% and 126% for F161 and F172, respectively, whereas it increased only by 28% for W880 (Table 2) (Fig. 1). Likewise, the positive effect of P. corethrurus on rice root biomass exhibited a 323% increase for N4 while this effect exhibited only a 19% increase for B22. A similar trend was observed for root P levels (Table 2). Regarding the shoot:root ratio, the effect of earthworms was highly variable and depended on specific rice cultivars (Fig. 1). It was either positive (B22, F161, and F182), neutral (F172) or negative (N4 and W880). Similarly, the response of rice cultivars to earthworms in terms of P acquisition efficiency was positive (B22, F161, and F172) or negative (F182, N4, and W880). It is interesting to note that, even if not significant according to two-way ANOVA, the magnitude of the increase induced by earthworms on shoot biomass, shoot P and shoot N amount also varied depending on rice cultivar (Fig. 1). For instance, the increase in shoot biomass induced by earthworms ranged from 40% (W880) to 129% (B22) according to the cultivars being examined. Likewise, the increase in shoot P amount in the presence of earthworms ranged from 37% (W880) to 145% (F161), and the increase in shoot N amount varied from 116% (W880) to 355% (B22) in the presence of earthworms.

Rice cultivars in the present experiment can be classified into three categories (Fig. 1

Phylogenetic, agronomic and ecological relationships

We did not find significant linear relationships for the ecological distances among rice cultivars (i.e., their ability to respond to earthworm inoculation), agronomic (R² = 0.15, Pvalue 0.144), and phylogenetic (R² = 0.10, P-value 0.242) distances (Fig. 2). However, the agronomic and phylogenetic distances were significantly correlated (R² = 0.56, P-value 0.001).

Discussion

Earthworms as plant promoters irrespective of rice cultivars

The earthworm survival rate, production of cocoons (1 to 4 cocoons per mesocosm) and surface casts in the mesocosms indicated that the conditions were favourable for the development and activity of earthworms during the experiment. Under these conditions, we demonstrated that the earthworm P. corethrurus strongly increased plant growth and nutrition regardless of rice cultivar. Increased rice growth was expressed by higher shoot biomass (99% increase), root biomass (93% increase) and total biomass (96% increase). We also found positive earthworm effects on leaf physiological traits, which indicated that earthworms enhanced photosynthetic light use efficiency and chlorophyll content in plants. The only plant traits that exhibited negative Cohen's d values in some cultivars were the leaf dry matter content, specific leaf area and P acquisition efficiency. [START_REF] Brown | Effects of earthworms on plant production in the tropics[END_REF][START_REF] Brown | How earthworms affect plant growth: burrowing into the mechanisms[END_REF] reviewed 246 experiments conducted in tropical countries and concluded that in 43% of these studies, earthworms enhanced biomass production by more than 20%. The same observation was noted by van Groenigen et al. ( 2014) in a meta-analysis of 58 studies published within one century . These authors pointed out that increased N mineralization was the main pathway for the positive effects of earthworms on plant growth. Likewise, in the present study, earthworm inoculation strongly increased shoot N amounts (+267%), and this plant trait had the highest percentage of variance explained by earthworms (79%).

A multiple nutrient-omission experiment that was conducted with the same soil showed that P was the main nutrient which limited rice growth [START_REF] Raminoarison | Multiple-nutrient limitation of upland rainfed rice in ferralsols: a greenhouse nutrientomission trial[END_REF]. It is thus more likely that the positive effects of earthworms on rice growth are mainly driven by improved P availability [START_REF] Chapuis-Lardy | Phosphorus transformations in a ferralsol through ingestion by Pontoscolex corethrurus, a geophagous earthworm[END_REF][START_REF] Ros | Exploring the pathways of earthworm-induced phosphorus availability[END_REF][START_REF] Vos | Large variations in readily-available phosphorus in casts of eight earthworm species are linked to cast properties[END_REF]. This hypothesis is supported by higher shoot P (87% increase) when P. corethrurus was inoculated. We also observed significant effects of earthworms on plant P acquisition efficiency. In our experiment, a large number of casts were observed (not quantified) at the end of the experiment, which support the hypothesis formulated by [START_REF] Vos | Do earthworms affect phosphorus availability to grass? A pot experiment[END_REF] and suggest that the increased plant P uptake was probably induced by the increase in available P in earthworm casts. The positive effect of earthworms on plant growth via increased soil P availability has been reported many times [START_REF] Graff | The phosphorus content of earthworm casts[END_REF][START_REF] Kuczak | Inorganic and organic phosphorus pools in earthworm casts (Glossoscolecidae) and a Brazilian rainforest Oxisol[END_REF][START_REF] Ros | Exploring the pathways of earthworm-induced phosphorus availability[END_REF][START_REF] Sharpley | Potential role of earthworm casts for the phosphorus enrichment of run-off waters[END_REF][START_REF] Sharpley | Seasonal variation in casting activity and in the amounts and release to solution of phosphorus forms in earthworm casts Soil[END_REF][START_REF] Van Groenigen | How fertile are earthworm casts? A meta-analysis[END_REF][START_REF] Vos | Large variations in readily-available phosphorus in casts of eight earthworm species are linked to cast properties[END_REF]Vos et al., 2014), including in Ferralsols (Chapuis-Lardy et al., 1998;[START_REF] Chapuis-Lardy | Modification of P availability by endogeic earthworms (Glossoscolecidae) in Ferralsols of the Malagasy Highlands[END_REF].

Plant breeding and rice ability to interact with earthworms

Despite the overall positive effects of earthworms on plants, the ability of rice to interact with earthworms varied by cultivar. These findings are in agreement with [START_REF] Noguera | Amplifying the benefits of agroecology by using the right cultivars[END_REF], who conducted a mesocosm experiment in Colombia with the same earthworm species but in a nutrient-rich soil and with other rice cultivars.

From our data, it is difficult to identify the mechanisms involved in the response variability of rice cultivars to earthworms. For instance, the P acquisition efficiency (PUE) was the plant trait for which the percentage of variance explained by earthworm-rice cultivar interaction was greatest (29%). The role of P, as mentioned earlier, thus appears to be central in earthworm-rice interactions in nutrient-depleted tropical soils [START_REF] Coulis | Endogeic earthworms modify soil phosphorus, plant growth and interactions in a legume-cereal intercrop[END_REF][START_REF] Le Bayon | Effects of earthworms on phosphorus dynamics-a review Dynamic[END_REF]. It would then be judicious to examine this trait. [START_REF] Vos | Large variations in readily-available phosphorus in casts of eight earthworm species are linked to cast properties[END_REF] listed the potential pathways for earthworm-induced enhanced soil P availability: (i) elevated pH (higher pH in casts) that affects concentrations of P ions in solution, (ii) dissolved organic carbon production by worms with similar effects through competitive adsorption, (iii) stimulated mineralization of organic P (enzymes) and (iv) selective feeding. In our study, given the equal survival rates of earthworms for the various treatments, it is very unlikely that the differences observed in the plant response to earthworms could arise from these mechanisms, which are specific to worms. In contrast, we believe that these differences could come from root trait variability, which is known to be affected by earthworms [START_REF] Arnone | Earthworm effects on native grassland root system dynamics under natural and increased rainfall[END_REF][START_REF] Junaidi | Root traits and root biomass allocation impact how wheat genotypes respond to organic amendments and earthworms[END_REF]. We can thus suppose that the colonization of casts by roots and their fungal endomycorrhizal symbionts could affect plant nutrition [START_REF] Milleret | Root, mycorrhiza and earthworm interactions: their effects on soil structuring processes, plant and soil nutrient concentration and plant biomass[END_REF][START_REF] Van Groenigen | Earthworms increase plant production: a meta-analysis[END_REF][START_REF] Zaller | Subsurface earthworm casts can be important soil microsites specifically influencing the growth of grassland plants[END_REF], especially plant P uptake [START_REF] Bolan | A critical review on the role of mycorrhizal fungi in the uptake of phosphorus by plants[END_REF][START_REF] George | Role of arbuscular mycorrhizal fungi in uptake of phosphorus and nitrogen from soil[END_REF][START_REF] Smith | Roles of arbuscular mycorrhizas in plant phosphorus nutrition: interactions between pathways of phosphorus uptake in arbuscular mycorrhizal roots have important implications for understanding and manipulating plant phosphorus acquisition[END_REF]. These root traits could vary according to rice cultivars. Knowing the crucial roles of these parameters in plant P acquisition [START_REF] Bolan | A critical review on the role of mycorrhizal fungi in the uptake of phosphorus by plants[END_REF][START_REF] George | Role of arbuscular mycorrhizal fungi in uptake of phosphorus and nitrogen from soil[END_REF] and their interaction with earthworms [START_REF] Milleret | Root, mycorrhiza and earthworm interactions: their effects on soil structuring processes, plant and soil nutrient concentration and plant biomass[END_REF], it would be interesting to further investigate these root traits, e.g., root surface, length, number of tips or mycorrhizal fungal colonization, in further studies to identify the mechanisms involved in the variability in earthworm-plant interactions with plant cultivars. It would also be interesting to monitor the P nutrition of rice during its growth, in the presence or absence of earthworms, for a reduced number of contrasting varieties. This could allow us to test whether the response of varieties to the presence of rice takes place at key phenological periods.

Considering the agronomic characteristics of rice cultivars (Table 2), we did not find evidence of relationships between some agronomic criteria and rice response to earthworms. Accordingly, we did not observe any significant relationship between the agronomic distances among cultivars and their ability to interact with inoculated earthworms. These results suggest that, regardless of the agronomic criteria focused on in the breeding programme, plant breeding may affect the ability of rice crops to exploit the beneficial functions achieved by earthworms. As plant breeding affects the genetic inheritance of rice cultivars with contrasting NUE or PUE, the cultivars can therefore exploit the presence of earthworms differently.

However, before taking this for granted, it would be beneficial to test this hypothesis with a larger panel of rice cultivars.

Ecological implications for agroecology and limits of the study

This experimental study showed that the upland rice cultivars commonly used by farmers in the Highlands of Madagascar have varying abilities to interact with P. corethrurus. This result is noteworthy because the cross effects of earthworms and rice cultivars were highly significant despite the relatively short duration of the study. To confirm these patterns and to measure rice yield, it would be beneficial to continue with an earthworm inoculation experiment in the field. Also, the low genetic diversity within our narrow cultivar panel could also be a factor that limited our conclusions. However, the criteria for choosing rice cultivars in this study were constrained by the genetic pool that was adapted to the environmental and agronomic conditions (climate, soil, uses and producer preferences) of the Highlands of Madagascar [START_REF] Raboin | Upland rice varieties for smallholder farming in the cold conditions in Madagascar's tropical highlands[END_REF]. This genetic diversity is low and confers significant risks for the production of rainfed rice, particularly against pests. In view of the major role of biological interactions between soil organisms and rice for the tolerance of rice to pests and diseases (Blanchart et al., 2019), considering the capability of varieties to interact with earthworms seems to be essential. In these conditions, however, we succeeded in identifying the rice cultivars that exhibited strong (N4 and F182), intermediate (F172, B22, and F161) and low (W880) abilities for interacting with earthworms. Integrating the most appropriate rice cultivars into relevant agroecological practices has been a concern of several soil ecologists and agronomists [START_REF] Loeuille | Eco-evolutionary dynamics of agricultural networks: implications for sustainable management[END_REF][START_REF] Noguera | Amplifying the benefits of agroecology by using the right cultivars[END_REF]. We therefore propose to consider the plant genetic material that best interacts with earthworms to intensify soil ecological processes in low-input tropical agrosystems, either for direct use with relevant agro-ecological practices or for inclusion in plant breeding programs. Such innovative practices may be a suitable approach to meet the constraints of the low input production systems of smallholder farmers in the Highlands of Madagascar. S2). The ecological distance is the Euclidean distance computed from the response of cultivars to earthworm inoculation using Cohen's d effect size for each rice trait (Fig. 1). All distances were bounded between 0.1 and 1 using homothetic transformation. N4, W880, F161, B22, N172 and F182 refers to rice cultivars (Table S1). 2.0 (0.5) 2.2 (0.3) Specific Leaf Area mm².mg -1 11.9 (1.4) 10.7 (1.9) 14.3 (1.5) 17.9 (8.9) 12 (2.2) 12.7 (2.7) 14.2 (1.6) 12.3 (1.4) 14.0 (2.5) 10.4 (1.6) 14.7 (3.9) 13.9 (3.0) Normalized Difference Vegetation Index Abs 0.025 (0.009) 0.039 (0.003) 0.029 (0.005) 0.039 (0.004) 0.029 (0.009) 0.043 (0.005) 0.030 (0.007) 0.049 (0.005) 0.028 (0.006) 0.051 (0.002) 0.030 (0.005) 0.047 (0.005) NDVI Abs 0.55 (0.1) 0.76 (0.02) 0.54 (0.07) 0.70 (0.08) 0.49 (0.04) 0.7 (0.04) 0.51 (0.08) 0.71 (0.04) 0.50 (0.05) 0.75 (0.03 0.61 (0.08) 0.70 (0.07) Shoot biomass mg 59.4 (4.7) 136 (29.2) 47.4 (8.3) 104.0 (40.4) 44.6 (10.8) 89.1 (15.7) 38.7 (5.9) 81.9 (11.0) 35.0 (9.5) 73.7 (5.6) 61.9 (16.1) 86.7 (8.0) Root biomass mg 83.9 (29.2) 99.6 (9.8) 54.0 (5.5) 90.6 (35.8) 48.3 (18.5) 94.1 (18.5) 48.3 (4.4) 107.0 (44.7) 33.9 (2.7) 143.2 (73.7) 66.7 (18.5) 113.8 (30.3) Shoot:root ratio ratio 0.78 (0.25) 1.37 (0.3) 0.85 (0.13) 1.16 (0.22) 0.98 (0.2) 0.98 (0.27) 0.81 (0.18) 0.9 (0.4)

N4-W880 F161-N4 N4-F172 N4-B22 F172-W880 F182-F172 F172-F161 F161-W880 F182-N4 F182-W880 B22-W880 F161-F182 B22-F182 B22-F161 B22-F172
1.03 (0.26) 0.68 (0.41) 0.96 (0.22) 0.81 (0.24) Shoot P amount µg-P.pot -1 46.7 (4.5) 95.8 (31.1) 35.2 (8.1) 86.1 (34.0) 30.0 (7.9) 66.7 (23.3) 39.3 (9.3) 56.0 (8.2) 31.2 (3.0) 58.6 (11.7) 42.8 (8.4) 58.4 (11.4) Shoot N amount mg-N.pot -1 0.65 (0.06) 2.94 (0.88) 0.58 (0.16) 2.39 (0.88) 0.48 (0.16) 1.88 (0.52) 0.45 (0.06) 1.72 (0.37) 0.40 (0.15) 1.68 (0.11) 0.82 (0.31) 1.78 (0.29) P uptake efficiency µg-P.g -1 of dry root 0.61 (0.23) 0.97 (0.33) 0.64 (0.11) 0.97 (0.15) 0.66 (0.18) 0.73 (0.25) 0.83 (0.27) 0.60 (0.24) 0.92 (0.04) 0.54 (0.34) 0.67 (0.14) 0.55 (0.18) N uptake efficiency mg-N.g -1 of dry root 8.56 (3.07) 29.68 (8.82) 10.56 (2.55) 27.50 (5.68) 10.20 (1.86) 20.42 (5.81) 9.46 (2.02) 18.92 (9.28) 11.72 (4.15) 15.52 (9.80) 12.38 (2.95)

  ): (i) rice cultivars with high average Cohen's d-values (response to earthworms), such as N4 and F182, with average d-values of 0.95 and 0.64, respectively; (ii) rice cultivars with intermediate responses, such as F172, B22, and F161, with average d-values of 0.52, 0.43 and 0.32, respectively; and (iii) rice cultivars with low average d-values, such as W880 (d = 0.20).

Fig. 1 .

 1 Fig. 1. Effect sizes (Cohen's d) of earthworms on different plant traits according to rice

Fig. 2 .

 2 Fig. 2. Relationships between phylogenetic, agronomic and ecological distances. The

  Photochemical Reflectance Index

Table 1 .

 1 Results of two-way ANOVA (eta² in % and p-value) for the main effects (rice cultivars and earthworms) and their interactions for each plant variable.

	Rice cultivars	Earthworms	Interaction	Residuals
	Eta 2$	p-value	Eta 2	p-value	Eta 2 p-value	Eta 2

$

Eta-squared (eta²) is a measure of effect size from ANOVA (% of variance explained) P-value thresholds: *** < 0.001; ** < 0.01; * < 0.05, ns: not significant

Table 2 .

 2 Mean (+-SD) for each plant variable according to treatments without earthworms (-EW) and with earthworms (+EW) after eight weeks of growth.

	Leaf Dry Matter Content	mg.g -1	2.4	(0.7) 2.8	(0.5)	2.7	(0.2) 2.9	(0.5)	2.1	(0.5) 2.4	(0.3)	2.1 (0.6) 2.0	(0.5)	2.3	(0.4) 2.1	(0.3)

  16.84 (6.22)

	Variables	Unit	Rice cultivars
			B22		F161		F172		F182		N4		W880
			-EW	+EW	-EW	+EW	-EW	+EW	-EW	+EW	-EW	+EW	-EW	+EW

Acknowledgements

We want to thank Eric Randrianasolo, Andrianantenaina Hilaire Damase Razafimahafaly and Marie-Paule Razafimanantsoa (Laboratoire des RadioIsotopes) for their technical assistance.

This study was funded by the Agropolis Foundation (Investissements d'Avenir Programme, ANR-10-LABX-0001-01) under the framework of the SECuRE (ID 1605-007) project. This work was also supported by the French Ministry Europe and Foreign Affairs under the programme 'Make Our Planet Great Again" for postdoctoral researchers.


Fanyu Huang
email: fanyu.huang@etu.univ-amu.fr

Marjorie Armando

Stéphane Dufau

Oleg Florea

Philippe Brouqui

Sophia Boudjema

Covid-19 outbreak and health care worker behavioral change toward hand hygiene practices

Keywords: Covid-19, real-time measurement, compliance, automated hand hygiene monitoring, cross-transmission, infection control

Background:

The coronavirus disease (COVID-19) pandemic has affected healthcare workers (HCW) in their clinical practice. HCW were challenged with new guidelines and practices to protect themselves from occupational risks. We wished to observe if hand hygiene behavior by real-time measurement was related to the dynamic of the epidemic, and the type of patient being cared for in France.

Methods: This study used an automated hand hygiene recording system to measure HCW hand hygiene on entry to and exit from patient rooms throughout the COVID-19 pandemic.

We analyzed the correlation between hand hygiene compliance and COVID-19 epidemiological data. Analysis of variance was performed to compare compliance rate during the different periods of the epidemic.

Findings: HCW hand hygiene rate on room entry decreased over time; on room exit, it increased by 13.73% during the first wave of COVID-19, decreased by 9.87% during the post-lockdown period, then rebounded by 2.82% during the second wave of the epidemic.

Hand hygiene during patient care and hand hygiene on room exit had a positive relationship with the local COVID-19 epidemic; conversely, hand hygiene on room entry did not depend on the trend of the epidemic, nor on nursing of COVID-19 patients, and it decreased over time.

Conclusion:

HCW modified their behaviors to face the risk propensity of the pandemic. However, to improve the poor compliance at room entry, reducing confusion between the hand hygiene recommendation and glove recommendation may be necessary; disinfection of gloving hands might solve this issue.

Introduction

Since the 2000's, coronaviruses (CoVs) have been associated with significant disease outbreaks in East Asia (SarS-CoV-1) and the Middle East (MERS-CoV). The spread of the novel coronavirus (SARS-CoV-2), initially identified in the Hubei province of China in December 2019, was declared by the World Health Organization (WHO) as the pandemic of coronavirus disease (COVID-19) in March 2020 [START_REF]Coronavirus Disease (COVID-19) Situation Reports n[END_REF]. At the time of writing there had been 91,938,218 cases and 1,967,655 deaths globally, including 2,806,590 cases and 68,802 deaths in France [START_REF]Deaths from COVID-19 Virus Pandemic -Worldometer[END_REF]. Healthcare workers worldwide, who have been regularly trained to avoid hospital-acquired infection by following guidelines, particularly hand hygiene, to reduce cross transmission and protect their patients are currently facing another objective: to protect themselves from SARS-CoV-2 infection using prevention protocols to which they are less commonly accustomed (self-protection). These new sanitary guidelines directed toward health care worker protection rather than toward patient protection is a new challenge for this community. With personal protection equipment (PPE), hand hygiene has been shown to be the cornerstone of protection from respiratory viruses [START_REF] Hirose | Survival of SARS-CoV-2 and influenza virus on the human skin: Importance of hand hygiene in COVID-19[END_REF][START_REF]Infection prevention and control during health care when novel coronavirus (nCoV) infection is suspected n[END_REF], and hand hygiene remains a main way to limit cross-transmission, as recommended by the WHO [START_REF]Infection prevention and control during health care when novel coronavirus (nCoV) infection is suspected n[END_REF].

Since 2012, we have developed an automated hand hygiene monitoring system and used it as a part of the management of healthcare-associated-infections at the University Hospital Institute Méditerranée Infection (IHU-MI) [START_REF] Brouqui | New Approaches to Prevent Healthcare-Associated Infection[END_REF][START_REF] Dufour | Evaluation of hand hygiene compliance and associated factors with a radio-frequency-identification-based realtime continuous automated monitoring system[END_REF][START_REF] Kerbaj | Smartphone text message service to foster hand hygiene compliance in health care workers[END_REF][START_REF] Boudjema | MediHandTrace ®: a tool for measuring and understanding hand hygiene adherence[END_REF]. The changing paradigm of hand hygiene practice imposed by this new ongoing epidemic seemed interesting to monitor with our system, to evaluate if HCW had (or not) easily adjusted to this new approach of infection prevention and changed their behaviour. Since we have observed two epidemic waves, we were interested in monitoring HCW in between the two waves to evaluate if their hand hygiene behavior correlated with the outbreak amplitude and with the type of patient being cared for.

This study aims to observe if hand hygiene practices on entry and exit of the patient's room and during patient care were correlated with the dynamic of the epidemic, and the type of patient being cared for (COVID-19 cases or not) throughout the two waves of the COVID-19 pandemic.

Methods

Automated hand hygiene recording systems

Since the end of 2017, an automatic hand hygiene monitoring device (MediHandTrace©) has been in place in the infectious diseases unit, which contains 25 single bedrooms. This system measures HCW utilization of alcohol-based hand rubs (AHR) on entry and exit from patient rooms (hand hygiene opportunity). Thanks to voluntary HCW who gave their consent, a unique ID tag is inserted in their shoes and when entering or exiting the bedroom of each patient's room, this ID tag, a door sensor and a sensor on the hand sanitizer, communicate through a server and allow identification of who entered or exited the room, and if AHR was performed on entry and exit, with a very good accuracy in experimental settings [START_REF] Dufour | Evaluation of hand hygiene compliance and associated factors with a radio-frequency-identification-based realtime continuous automated monitoring system[END_REF][START_REF] Kerbaj | Smartphone text message service to foster hand hygiene compliance in health care workers[END_REF][START_REF] Boudjema | MediHandTrace ®: a tool for measuring and understanding hand hygiene adherence[END_REF][START_REF] Dufour | Input of Innovative Technology for Surveillance and Improvement of Hand Hygiene: The Medihandtrace Contribution to Hand Disinfection Monitoring and Intervention[END_REF].

However, in the real-life environment, the system does not tend to perform as well, especially when several HCW enter the room at the same time. Indeed, sensor events like "the door is opening" and "the door is closing" are not associated with an ID tag, and therefore cannot be directly linked to a particular HCW, leaving issues such as whether or not the person whose behavior is being evaluated truly exited the room.

To optimize the accuracy of interpretation of HCW activities, we developed an algorithm written in C++ programming language that identifies each activity by analysis of short sequences of consecutive events from raw sensor data. Sensor events were grouped in sequences defined as a serial of signals traducing an event (the door is opening, an identified HCW puts their shoes on the carpet, he/she uses hydroalcoholic solution, etc.) associated with its corresponding time of occurrence.

Such event grouping enabled us to accurately pair entry and exit events with unique ID tags in the single bedroom / multiple HCW scenario. It was thus possible to follow the nursing staff's activities in a bedroom on an individual basis, for instance, for each HCW, to know whether they washed their hands when they entered and when they left the room. To assess the accuracy of the optimization algorithm, we compared its interpretation to a human-based video analysis from cameras set up in patients' rooms. Level of correspondence was excellent.

Piloting of the automated system

In order to assess accuracy of data capture, we examined 33 randomly selected HCW events occurring between 26th November to 29th November 2019 and compared video and interpretations from the algorithm. Eighteen room entries were correctly interpreted as such by the algorithm; for room exits, 13 were interpreted correctly but 2 interpretations were erroneous due to several HCW exiting at the same time. As a result, 93.9% of entries and exits were interpreted correctly by the algorithm and the kappa coefficient between the videos and interpretations from the algorithm was 0.88 (Supplementary material).

Infection control procedures

During the COVID-19 pandemic, HCW were trained and encouraged to adhere to the principles of WHO evidence-based guidelines for PPE use and hand hygiene practice [START_REF]Rational use of personal protective equipment for coronavirus disease (COVID-19) and considerations during severe shortages n[END_REF][START_REF]WHO guidelines on hand hygiene in health care[END_REF].

HCW were asked to wear PPE (gown, FFP2 mask and gloves) before entering patient rooms.

Hand sanitizers containing alcohol (75-85% v/v) effectively reduce the infectivity of coronaviruses in vitro [START_REF] Kratzel | Inactivation of Severe Acute Respiratory Syndrome Coronavirus 2 by WHO-Recommended Hand Rub Formulations and Alcohols[END_REF]. Disinfection of gloved hands has been demonstrated as efficient and feasible during patient care for multiple activities, and a recent study shows that alcoholbased solution did not affect elongation at breakage of the nitrile gloves [START_REF] Kampf | Disinfection of gloved hands for multiple activities with indicated glove use on the same patient[END_REF][START_REF] Garrido-Molina | Disinfection of gloved hands during the COVID-19 pandemic[END_REF][START_REF] Assadian | Disinfection of artificially contaminated gloved hands reduces transmission of Staphylococcus epidermidis to catheter valves[END_REF]. Thus, we promoted the use of gloved AHR upon entry to the room, upon exit of the room and as often as necessary during patient care.

Definitions

Daily hand hygiene compliance rate on room entry and exit was computed by the daily number of AHR utilizations on entry and exit, divided by the total daily number of entries and exits. AHR during care were computed by the number of AHR recorded by our system after 18 seconds (grace delay period) from entering divided by the total daily number of room entries. AHR consumption was computed by the total volume (1 application of AHR=3ml) of AHR by each HCW each day.

The epidemiological COVID-19 data of our hospital was based on the monthly number of patients screened and the number of patients diagnosed positive for SARS-CoV-2, obtained from the hospital information system. To calculate nursing care of the COVID-19 patient, the bed-day total was calculated as the daily number of beds occupied by either a COVID-19 or a non-COVID-19 patient admitted as an inpatient each month. We then separated the study into

Statistical analysis

Data analysis included descriptive analyses. The assumption of normality was assessed by analysis of skewness and kurtosis. First, to evaluate the relation between the local COVID-19 epidemic and hand hygiene behaviors, the Pearson correlation coefficient was used to evaluate the strength of the relationship between the compliance with AHR (on entry and exit), the number of patients screened, the number of patients diagnosed as positive for SARS-CoV-2 and the total bed-day of care of each COVID-19 patient. Second, comparing any differences in compliance with AHR between the four COVID-19 periods, analysis of variance (ANOVA) was used to compare the mean of compliance with AHR (on entry, during care and on exit) and AHR consumption between these periods. Time series analysis using autoregressive integrated moving average (ARIMA) model was performed to analyze the trend of hand hygiene compliance over time. Results were considered statistically significant at p-values less than 0.05. All the collected data were entered into an Excel file and the statistical tests were performed with SPSS 25.

Ethics

The study protocol was approved by the Review Board of our institution and available under N° 2016-018; all participating HCW were informed about the automatic monitoring procedure and the guarantee of anonymity and confidentiality. Video was recorded and visualized for accuracy evaluation of the algorithm by two researchers not involved in patient care (MA and FH). Once the content was analyzed and anonymized, the recording video was destroyed. All HCW are protected by the French National Commission on Informatics and Liberty.

Results

Evolution of compliance with hand hygiene

From September 2019 to November 2020 (over 15 months of real-time observation), a total of 162 334 entries and exits were recorded by the automatic monitoring system. The mean of compliance with AHR use on entry to a patient's room within this period of observation was 21.02% (SD= 8.91) and on exit from a patient's room was 55.03% (SD= 11.9). During care, mean incidence of AHR use by HCW was 4.32% (SD=2.34). Mean AHR consumption was 61.63(SD= 22.45) mL/HCW/day. Figure 1 shows the evolution of compliance with AHR use on room entry, during patient care and on room exit.

Epidemiological data

From December 2019 to November 2020, 253547 new patients were screened at IHU-MI and 21938 patients were diagnosed as SARS-CoV-2 positive. A total of 1319 patients were admitted to our unit including 834 COVID-19 patients. Each month, the average number of patients screened was 16903 (SD= 18654) and the average number of COVID-19 patients was 1466 (SD= 2058) (Supplementary material). The average number of bed-days was 730 (SD=123) per month, including 313 (SD=265) bed-days for non-COVID-19 patients and 417 (SD= 330) bed-days for COVID-19 patients (Figure 2).

Compliance with AHR use on room exit had a positive correlation with the number of patients screened (r=0.66, p=0.004), the number of patients diagnosed (r=0.53, p=0.021) and the total number of bed-days of COVID-19 patients (r=0.68, p=0.011). Use of AHR during care had a strong positive correlation with the number of patients screened (r=0.84, p<0.001), the number of patients diagnosed (r=0.77, p<0.001), the number of bed-days of COVID-19 patients (r=0.88, p<0.001) and the moderate positive relation with total number of bed-days of care (r=0.57, p=0.033). AHR consumption had a positive correlation with the number of beddays of COVID-19 patients (r=0.63, p=0.019) and total bed-days of care (r=0.61, p=0.023).

Compliance with AHR use on room exit and AHR use during patient care increased as the epidemic of COVID-19 increased or the nursing of COVD-19 in the unit increased, and vice versa. AHR consumption increased when the total number of bed-days or the nursing of COVID-19 patients increased. However, compliance with AHR use on room entry was not associated with the COVID-19 epidemic or the nursing of COVD-19 in the unit (Table I).

The mean of compliance with AHR use on room entry was 23.88% (SD=7.56) during the pre-COVID-19 period. For the first wave of COVID-19 this was 27.31% (SD=6.45), for the postlockdown period 17.3% (SD=6.77) and for the second wave was 13.3% (SD=6.27) (F(3,435) = 77.93, p < 0.001). This low compliance rate on room entry could be explained by the fact that HCW were gloved before entering the room and staff were not used to disinfecting gloved hands. The mean rate of AHR use during patient care was 3.21% (SD=1.43) at the pre-COVID-19 period; for the first wave of COVID-19 this was 5.37% (SD=2.11), for the postlockdown period 4.41% (SD=2.15) and for the second wave 5.17% (SD=1.83) (F(3,435) = 37.36, p <0.001). The mean of compliance with AHR use on room exit was 50.63% (SD=8.28) for the pre-COVID-19 period; for the first wave of COVID-19 this was 64.37% (SD=8.27), for the post-lockdown period 54.5% (SD=8.52) and for the second wave 57.32% (SD=9.93) ( F(3,435) = 51.57, p < .001). Mean AHR consumption was 60.28 (SD=22.75) mL/HCW/day for the pre-COVID-19 period; for the first wave of COVID-19 this was 69.42 (SD=18.74) mL/HCW/day, for the post-lockdown period 54.94 (SD=15.97) mL/HCW/day and for the second wave, 66.98 (SD=21.83) mL/HCW/day (F(3,435) = 9.578, p < .001) (fig. 3).

Mean rate of AHR use on room entry increased by 3.43% during the first wave of COVID-19 but got lower over time. Mean rate of AHR use during patient care increased by 2.15% during the first wave of COVID-19, decreased by 0.95% during the post-lockdown period, and then rebounded by 0.76% during the second wave of the epidemic. Mean rate of AHR use on room exit increased by 13.73% during the first wave of COVID-19, decreased by 9.87% during the post-lockdown period, then rebounded by 2.82% during the second wave of the epidemic.

Concerning AHR consumption, this increased by 9.14 mL/HCW/day during the first wave of COVID-19, decreased by 14.48 mL/HCW/day post-lockdown and then rebounded by 12.05 mL/HCW/day during the second wave of the epidemic. Time series analysis confirmed that there was a decrease of compliance with AHR use on room entry over time (P<0.001) and an increase of compliance with AHR use on room exit over time (p=0.013)

Discussion

This long-term hand hygiene observation using data from an automated monitoring system shows that HCW use of AHR during patient care and on room exit were positively correlated with the dynamics of the local COVID-19 epidemic and the nursing of COVID-19 patients.

Total AHR consumption appeared to be related to the nursing of COVID-19 patients and the total number of bed-days of care. Conversely, AHR use on room entry did not depend on the trend of the epidemic nor nursing of COVID-19 patients. As a result, rates of AHR use on both room entry and room exit increased during the first wave of the epidemic and both decreased during the post-lockdown period, while AHR use on room exit and during care tended to follow the trend of the epidemic; AHR use on room entry decreased over time.

Four recent studies found that HCW hand hygiene compliance improved during the early pandemic (first quarter of 2020); however, three of these studies were observed by audit without comparing with any remarkable events in national COVID-19 control [START_REF] Israel | Dramatically improved hand hygiene performance rates at time of coronavirus pandemic[END_REF][START_REF] Derksen | Obstetric Healthcare Workers' Adherence to Hand Hygiene Recommendations during the COVID-19 Pandemic: Observations and Social-Cognitive Determinants[END_REF][START_REF] Wong | Is it possible to achieve 100 percent hand hygiene compliance during the coronavirus disease 2019 (COVID-19) pandemic?[END_REF][START_REF] Moore | The impact of COVID-19 pandemic on hand hygiene performance in hospitals[END_REF]. One study which was based on an automated monitoring system obtained a similar result to ours.

The authors found decreased hand hygiene performance after school closures, and concluded that even during the global crisis, it seemed difficult to maintain improved hand hygiene performance [START_REF] Moore | The impact of COVID-19 pandemic on hand hygiene performance in hospitals[END_REF]. Automated monitoring does afford some advantages during the pandemic, such as reducing the human cost for audit, continued measurement and reducing the Hawthorne effect [START_REF] Kratzel | Inactivation of Severe Acute Respiratory Syndrome Coronavirus 2 by WHO-Recommended Hand Rub Formulations and Alcohols[END_REF].

Our finding shows the different evolution of four hand hygiene indicators: compliance with AHR use on room entry, AHR use during patient care, AHR use on room exit and total AHR consumption. AHR use on room entry and during patient care are mainly related to patient protection whereas AHR use on room exit is related to self-protection of HCW. At the beginning of the epidemic, the improvement of both self-protection and patient-protection measures could be explained by HCW fear of the crisis, to avoid transmitting the virus to their family, to themselves or to their patients. A recent psychology study showed that fear of pandemic encouraged recommended public health behaviors due to the negative emotions that reduce motivation for risky behaviors [START_REF] Harper | Functional Fear Predicts Public Health Compliance in the COVID-19 Pandemic[END_REF]. It could be also explained by respect of the protocol. Among all required PPE within the COVID-19 protocol, our observations show a correlation between AHR use and the hospitalization of COVID-19 patients in the unit, with hand hygiene being performed frequently as recommended by the WHO [START_REF] Cavanagh | Rational hand hygiene during the coronavirus 2019 (COVID-19) pandemic[END_REF].

The second observation was the different evolution of compliance with AHR use at room entry and room exit. It seems that the COVID-19 outbreak had more impact on compliance with AHR use on room exit and during care, and on total AHR consumption. HCW were asked to wear PPE before entering a patient's room and then to remove gloves and apply AHR before leaving a patient's room; this protocol was respected. Thus, even with the drop in compliance during the post-lockdown period, the AHR use on room exit and during patient care remained higher during the second wave of the epidemic than during the pre-COVID-19 period.

Under those circumstances, it seems that gloving hands cause the reduction of compliance at entry. After the first wave of the epidemic, HCWs disinfected their hands less and less on room entry. The low compliance rates on entry could be explained by the gloved hand which has been reported to reduce hand hygiene [START_REF] Fuller | The Dirty Hand in the Latex Glove": A Study of Hand Hygiene Compliance When Gloves Are Worn[END_REF]. Moreover, one can imagine that HCW better perceived the risk to be exposed to the virus for themselves than to protect the patients. However, several recent studies showed the benefit of disinfection of gloved hands [START_REF] Baloh | Hand hygiene before donning nonsterile gloves: Healthcare workers' beliefs and practices[END_REF][START_REF] Jain | Modified glove use for contact precautions: Health care workers' perceptions and acceptance[END_REF][START_REF] Acquarulo | Mixed-methods analysis of glove use as a barrier to hand hygiene[END_REF]; alcohol-based disinfectants may slightly affect the breaking load of nitrile gloves, but it does not affect its extensibility [START_REF] Garrido-Molina | Disinfection of gloved hands during the COVID-19 pandemic[END_REF]. It seems our HCW were not aware on such evidence on room entry. As noticed by Allegranzi et al. hand hygiene appears neglected when the emergent virus seems to disappear with compliance rates becoming lower, which ties in with our observations. The studies of Maltezou et al. shows there are gaps in infection control in non-COVID-19 referral hospitals; it is possible that adherence to recommendations could be even lower in non-COVID-19 hospitals [START_REF] Maltezou | Hospital factors associated with SARS-CoV-2 infection among healthcare personnel in Greece[END_REF].

Conclusion

In conclusion, HCW respected the protocol and modified their behaviors during the outbreak; however, improvements of compliance with AHR on both room entry and exit were not sustained throughout the epidemic especially for entry. This pandemic has led HCW to adapt their hand hygiene behavior to the visible risk (the epidemic's curve) to protect themselves; according to our finding, we enforce the importance of hand hygiene monitoring even during the pandemic, especially before patient contact. To reduce potential confusion between the hand hygiene recommendation and glove recommendation, disinfection of gloving hands might improve poor compliance at entry.

  four periods: (1) pre-COVID-19, from September 2019 to the end of February 2020; (2) the first wave of COVID-19, from March 2020 to the end of May 2020; (3) post-lockdown, from June 2020 to the end of August; (4) the second wave of COVID-19, from September 2020 to the end of November 2020.

Fig. 1 :

 1 Fig.1: The evolution of the compliance to AHR use on room entry, during patient care and on room exit; 95% confidence interval.The green line represents AHR rates of use on room exit; the blue line represents AHR rates of use on room entry. The vertical dashed lines represent the different periods of the epidemic.

Fig. 2 :

 2 Fig.2: The evolution of bed-days of care The green line represents the total number of bed-days of care, the red line represents the beddays of care of COVID-19 patients and the blue line represents the bed-days of care of non-COVIV-19 patients. The vertical dashed lines represent the different periods of the epidemic.

Fig. 3 :

 3 Fig.3: Boxplots and mean plots (a.) AHR use on room entry (%), (b.) AHR use during patient care (%), (c.) AHR use on room exit and (%), (d.) AHR consumption (mL/HCW/day) in four periods of the COVID-19 epidemic.

Table I . Correlations between the monthly data of AHR use on room entry, AHR use during patient care, AHR use on room exit, number of patients screened, number of patients diagnosed, bed-days of COVID-19 patients and total bed-days of care.

 I

			AHR on entry AHR on exit	AHR during care AHR consumption Patients screened Patients diagnosed COVID patients
	AHR on exit	Pearson Correlation	,211	1
		(p values)	,226
		N	15	15
	AHR during Care	Pearson Correlation	-,307	,782 **	1
		(p values)	,133	,000
		N	15	15	15
	AHR consumption	Pearson Correlation	,203	,561 *	,298	1
		(p values)	,234	,015	,140
		N	15	15	15	15
	Patients screened	Pearson Correlation	-,310	,656 **	,842 **	,290	1
		(p values)	,131	,004	,000	,147
		N	15	15	15	15	15
	Patients diagnosed	Pearson Correlation	-,360	,529 *	,769 **	,329	,915 **	1
		(p values)	,093	,021	,000	,116	,000
		N	15	15	15	15	15	15
	COVID patients	Pearson Correlation	-,165	,676 *	,882 **	,628 *	,932 **	,848 **	1
		(p values)	,314	,011	,000	,019	,000	,000
		N	11	11	11	11	11	11	11
	Bed-days of care	Pearson Correlation	-,022	,465	,573 *	,612 *	,493	,393	,659 *
		(p values)	,475	,075	,033	,023	,062	,116	,014
		N	11	11	11	11	11	11	11

Acknowledgements

We thank the nurses and all the medical team at the Institute Méditerranée-Infection University Hospital for their willingness to participate and cooperate in this research. We thank David Braustein for the epidemiological data. We thank Dr Aileen McGonigal for English language editing.

Financial support

This study was funded by ANR-15-CE36-0004-01 and by ANR "Investissements d'avenir", Méditerranée infection 10-IAHU-03 and in part by SHARP-JA, Grant Agreement EC n° 848096.

Contributors

Conceived and designed the experiments: PB, FH, SB. Performed the experiments: FH, OF.

Algorithm developed: SD and MA. Analysed the data: FH. Wrote the paper: FH, PB, SB, MA.

Conflict of Interest

P Brouqui was a former advisor of the Medihandtrace® Company.