Fre Borea

Charlotte Chazeau

Guy Duhamel

Johanna Faure

Andréa Filippo

Nicolas Gasco

Alexis Martin

Félix Massiot-Granier

Clara Péron

Patrice Pruvost

Jules Selles
email: jules.selles@mnhn.fr

CPUE STANDARDISATION OF THE SOUTHERN INDIAN OCEAN ST. PAUL AND AMSTERDAM ROCK LOBSTER FISHERY

Abstract

This study reports on the analysis of long-term temporal trend in Catch Per Unit Effort (CPUE) for rock lobster caught in Saint Paul and Amsterdam (SPA) islands. CPUE standardization was performed using generalized linear models (GLM) fitted on catch and effort data for the period 1980-2019. Lognormal model was used to standardize the nominal CPUE using fishing year, fishing period, fishing area, and fishing year-area interactions as exploratory variables. For both islands a decline of standardised CPUE was observed at the beginning of the series followed by a relative stable trend with low variability until the recent years where an increase has been observed. The recent increase in both islands has been mainly driven by the offshore areas while a slight decline in the coastal area has been observed since 2016. These results suggest that the current stock level of the exploitable biomass of lobster in Saint Paul and Amsterdam have slightly increased in recent years.

Introduction

The commercial Catch Per Unit of Effort (CPUE) series of a resource is commonly employed as an index of population local abundance and integrated to the assessment of several exploited fish and invertebrate stocks. However, a number of factors besides density may influence the values of nominal CPUE including factors which affect catchability and availability. Standardisation procedures using General Linear Models (GLM) have been widely applied to commercial catch/effort data to produce reliable relative abundance index from nominal CPUE (e.g. [START_REF] Maunder | Standardizing Catch and Effort Data: A Review of Recent Approaches[END_REF][START_REF] Tascheri | Statistical models to stan-dardize catch rates in the multi-species trawl fishery for Patagonian grenadier (Macruronus magellanicus) off southern Chilean[END_REF][START_REF] Brodziak | Model selection and multimodel inference for standardizing catch rates of bycatch species: a case study of oceanic whitetip sharkin the Hawaiibased longline fishery[END_REF]. This document reports an application of a GLM standardization to rock lobster (Jasus paulensis) CPUE data from the French trap fishery in the Economic Exclusive Zone (EEZ) of Saint-Paul and Amsterdam (Figure 1) for the period 1980-2019.

Methodology

The fishery SPA islands are part of the French Southern and Antarctic Territories (TAAF) and are located in the subtropical zone of the South Indian Ocean. Although the islands cover respectively a limited area of 8 and 58 km2, the exclusive economic zone (EEZ) to which they belong covers 509 000 km² extending from 34° 30 'to 42 ° 00 South and 73° 12' at 81° 45 'East. Initially focused on the exploitation of fur seals (Arctocephalus tropicalis) and demersal fishes, these islands have been exploited annually for rock lobsters since 1948. Management decisions taken by the TAAF are based on the scientific expertise of the Museum National d'Histoire Naturelle (MNHN). The fishery is managed by setting annual allowable catches (TAC) for the rock lobster1 as well as technical prescriptions to control the fishing effort (e.g. fishing period, authorized fishing gear, mandatory fishing logbook, trap mesh size, legal size, control of discards) with the support of onboard fishing controllers on 100% of the fishing trips and landing controls. Recent TACs were shared between two fishing companies SAPMER and ARMAS PECHE which charter the fishing vessel.

The fishing fleet is composed of a single mother ship, currently the "Austral 2", owned by SAPMER, which targets and lands mainly rock lobster fished from 4 coastal (operating in depth inferior to approximatively 50m) canots (doris) setting wooden traps in the kelp zone (coastal area) and 2 pilothouse fishing boats (''caseyeurs'') in the deep area (operating in depth from approximatively 50 to 350m) with line of 20 steel traps2 (Figure 2). Rock lobsters are transhipped and weighted to the ''Austral 2'' where catches are proceeded on the on-board factory. Fishing takes place during the austral summer between end of November of the year N and May of the year N + 1 during which time the ''Austral 2'' makes two fishing trips of approximately the same duration (less than 2 months).

Data

An observation program of all fishing activity has been in operation since 1948 in SPA and all data have been integrated into the MNHN PECHEKER database since 1980 [START_REF] Martin | Pecheker, relational database for analysis and management of fisheries and related biological data from the French Southern Ocean fisheries monitoring scientific programs[END_REF]. Onboard observers collect fine-scale data on catch (in weight), effort (in number of trap) and biometry of the target species (rock lobster) and on bycatch which are relatively small, few tons of octopus (Octopus vulgaris) representing less than 5% of the catch.

As detailed above, the fishery involves different types of small fishing vessels operating at different scales in different areas, therefore the ideal scale of analysis would be the fishing operation. However, since the rock lobsters are processed and weighted daily on the Austral during the transshipment operation, our preliminary approach uses data aggregated per day. Data per fishing operation, would allow us to explore the variability of the CPUE deeper, but would require assumptions on the distribution of the catches between boats and trap lines.

The daily data used in our approach includes total rock lobsters catches, number of traps, fishing area (coastal or deep), octopus CPUE and fishing trip.

Accounting for historic change in technical requirements

Although the characteristics of the fishery (gear, number of boats, fishing season, etc.) have changed little over the past 40 years, recent changes in technical requirements may have had an effect on nominal CPUE. The processing coefficients for the different products (rock lobster tail, whole rock lobster) have been readjusted every fishing trip since the 2014/2015 season, with an average value of 3.34, whereas it was previously set at 3 affecting the estimated gross weight (see Table 1 for summary of processing coefficients and Annex 1 for adjusted catch and CPUE series).

Standardisation model

Nominal CPUE Arithmetic mean (Eq. 2) CPUE is calculated and used as the nominal nCPUE by island as the total catch for the year y divided by the total effort in year y:

𝐶𝑃𝑈𝐸 𝑦 = 1 𝑛 ∑ 𝑐𝑎𝑡𝑐ℎ.𝑎𝑑𝑗 𝑖,𝑦 𝑒𝑓𝑓𝑜𝑟𝑡 𝑖,𝑦 𝑛 1 (Eq 2)
Where 𝑐𝑎𝑡𝑐ℎ. 𝑎𝑑𝑗 𝑖,𝑦 is the adjusted catch (in kg) for each fishing day i in year y, efforti,y is the number of traps for each fishing day i in year y, and, n is the number of day fished in year y.

Standardised CPUE

Standardised CPUE is calculated from a GLM3 assuming a lognormal error distribution. Fishing year, fishing trip, fishing area and interaction between year and area were included in the GLM analyses as main explanatory variables. We also explored the effect of octopus predation on rock lobster catch rates using CPUE as a proxy of octopus densities, as reported in others studies (e.g.

Briceno et al. 2016). Variables describing gear configuration have been excluded since fishing

areas correspond strictly to the operation of two fleets (caseyeurs and canots) which operates different kind of traps. Furthermore, the same vessels, traps and fishing methods have been used

throughout the time series at the same time of the year.

The GLM used to standardised CPUE is given by the following: ln(𝐶𝑃𝑈𝐸) = µ + 𝛼 𝑦𝑒𝑎𝑟 + 𝛽 𝑓𝑖𝑠ℎ𝑖𝑛𝑔 𝑡𝑟𝑖𝑝 + 𝜂 𝑎𝑟𝑒𝑎 + 𝜑 𝐶𝑃𝑈𝐸 𝑜𝑐𝑡𝑜𝑝𝑢𝑠 + 𝛾 𝑦𝑒𝑎𝑟 * 𝑎𝑟𝑒𝑎 + 𝜀 (Eq. 3)

Where µ is the intercept,

Fishing year is a factor with 39 levels associated with the years (i.e. the fishing years:

1980/1981 to 2019/2020),

Fishing trip is a factor with 2 levels associated with the fishing periods (M1: December to January-February and M2: February to March-April),

Fishing area is a factor with 2 levels associated with fishing areas around SPA (coastal <50m, deeper area >50m around the islands. The offshore bank area, 16 miles bank (situated about 16nm southeast of Saint-Paul) have been excluded from the analysis, CPUE octopus is the proxy of octopus densities, and, ε is the model residuals.

Forward selections based on AIC were used to determine the variables that contributed significantly (p < 0.0014 ) to the deviance explained. In this document, the CPUE has been standardised on the year 1980, the first fishing trip and fishing area offshore bank for Saint Paul and coastal area for Amsterdam.

For this model, because of the fixed effect interaction of area with year (which implies changing spatio-temporal distribution patterns), an index of overall abundance needs to integrate the different trends in density in each area over the size of these areas. Accordingly, the standardised CPUE series is obtained from:

𝐶𝑃𝑈𝐸 𝑦 = [∑ 𝑒 (µ+ 𝛼 𝑦𝑒𝑎𝑟 + 𝛽 𝑓𝑖𝑠ℎ𝑖𝑛𝑔 𝑡𝑟𝑖𝑝 +𝜂 𝑎𝑟𝑒𝑎 +𝜑 𝐶𝑃𝑈𝐸 𝑜𝑐𝑡𝑜𝑝𝑢𝑠 + 𝛾 𝑦𝑒𝑎𝑟 * 𝑎𝑟𝑒𝑎 ) 𝑎 * 𝐴 𝑎 ] 𝐴 𝑡𝑜𝑡𝑎𝑙 (Eq. 3)
Where Aa is the surface of the zone a (coastal and deep), and, Atotal is the total size of the fishing ground considered (the division by Atotal is to keep the units and size of the standardised CPUE index comparable with those of the nCPUE). Table 2 provides the fishing area values for each fishing ground in SPA.

Results

The nominal CPUE time series shows a clear decrease at the beginning of the time series, following by a relatively stable period even though there were some oscillations and variability between years and an increasing trend in the most recent years (Annex 1). Furthermore, the first fishing trip (November to January) appears to have a higher CPUE over the overall period as well as the offshore area especially in the last year (Annex 2, Annex 3). The octopus CPUE appears to be highly negatively correlated to rock lobster CPUE at Amsterdam while it had no significant effect in Saint-Paul (Annex 5).

All of the variables considered are highly significant (p < 0.001) and are supported by stepwise AIC selection procedure (Table , Table) and explained approximately 50% of the variance with a pseudo5 R² of 0.51 and 0.46 for Saint and Amsterdam respectively.

The Pearson residuals for the lognormal model show a reasonable distribution for the Amsterdam stock, whereas the distribution of the Saint Paul stock is slightly skewed toward the negative values (Annexes 5, 6).

Nominal and standardized CPUE (together with 95% C.I.) for rock lobster are presented by Islands in Table , Table 5 andFigure 3, Saint Paul quite especially in the last year while the difference between coastal and offshore areas appears to be less pronounced at Amsterdam. The larger size of the lobsters present in the deep zone of Saint Paul explains this effect (Annex 7). Finally, the CPUE displays a negative linear relationship with octopus CPUE supporting that the capture of rock lobster using traps is affected by predation of octopus that occur inside fishing gear.

Discussion

From the preliminary analyses of this paper, the new GLM standardised CPUE series are put forward as a good index of abundance upon which to base future assessment of the population.

For the two islands, the standardised CPUE indices show an initial decrease, followed by a relative stable trend over the years with an increase trend in the most recent years suggesting that the current adult stock size of lobster grows.

Future work

Information from fine scale spatial distribution of fishing effort as well as gear setting, configuration and fishing masters are available since 2014 and should be integrated in the CPUE standardization. CPUE at the fishing operation level should be analysed considering for each fishing area as independent management unit. These data need to be analysed further to try to use them to estimate and account for the relative availability of the resource (i.e. lobster distribution) as well catchability (i.e. fishing power, fisher ability etc.). Furthermore, environmental information should be integrated to explore notably the relation between rock lobster distribution and the benthic habitats. Also, the weather and sea conditions play also an important role in the spatial distribution of fishing effort especially in the coastal area where small ''canots'' operate. Table 1: Conversion coefficients of the different rock lobster products in the SPA fishery.

Tables

Period

Annexes

Annex 1: Time-series of catch (t, in black) and adjusted catch (in red), CPUE (kg/trap, black dotted line) and adjusted CPUE (red dotted line) for the St. Paul and Amsterdam rock lobster.

  4. The nominal and standardised CPUE time-series are similar, but diverge notably in the last year.

Figure 4

 4 Figure 4 and 5 shows the effects of the variables on CPUE included in the standardisation process. The first fishing trip appears to have a higher CPUE, which could indicate potential local depletion in fishing areas throughout the season. The offshore area shows higher CPUE at

Figure 1 :

 1 Figure 1: Location of St. Paul and Amsterdam within the French EEZ in the South Indian Ocean.The French EEZ is delineated by a grey dashed line.

Figure 2 :

 2 Figure 2: Location of fishing area around St. Paul and Amsterdam islands. Coastal and deep fishing area are represented in blue and light blue respectively.

Figure 3 :

 3 Figure 3 : Comparative plot of the nominal CPUE (black dots) and GLM standardised CPUE series (black line) for Amsterdam Island with 95th confidence interval (dashed lines).

Figure 4 :

 4 Figure 4 : Comparative plot of the nominal CPUE (black dots) and GLM standardised CPUE series (black line) for Saint Paul Island with 95th confidence interval (dashed lines).

Figure 4 :

 4 Figure 4 : Partial plot (residuals) of main categorical effect on the CPUE for Saint Paul Island with 95 th confidence interval (grey area).

Figure 5 :

 5 Figure 5 : Partial plot (residuals) of main categorical effect on the CPUE for Amsterdam Island with 95 th confidence interval (grey area).

Table 2 :

 2 The size (km²) of each fishing area around Saint Paul and Amsterdam islands estimated from position of fishing operation from 2014/2015 to 2017/2018.

		Product	Coefficient
		whole cooked	1.10
	2014/2015 -2019/2020	gross tail	3.37
		half lobster	1.18
		whole cooked	1
	1980/1981 -2014/2015	whole gross gross tail	1 3
		cooked tail	3
	Island	Fishing area	Size (km²)
	Saint Paul	Coastal area	14.2
	Saint Paul	Deep area	215.5
	Saint Paul	16 miles Bank	92.3
	Amsterdam	Coastal area	24.2
	Amsterdam	Deep area	90.6

Table 3 :

 3 Summary table of the final model retained by forward selection based on AIC for SaintPaul standardised CPUE models using fishing year, fishing trip, fishing area as explanatory variables.

	Variable	DF	Residual Deviance	AIC
	NULL		693.7	4083.8
	Fishing_year	39	417.4	2690.6
	Fishing_trip	1	383.5	2447.5
	Fishing_area	1	366.9	2321.4
	Fishing_area * Fishing_year	39	337.6	2156.8

Table 4 :

 4 Summary table of the final model retained by forward selection based on AIC forAmsterdam CPUE models using fishing year, fishing trip, fishing area as explanatory variables.Independent explanatory variables are listed in the order of acceptance to the model.

	Variable	DF	Residual Deviance	AIC
	NULL		674.9	3906.0
	Fishing_year	39	423.1	2682.6
	Fishing trip	1	389.9	2480.4
	Fishing_area	2	378.4	2389.7
	CPUE octopus	1	377.5	2385.6
	Fishing_area * Fishing_year	39	347.5	2300.2

Table 5 :

 5 Standardised CPUE and nominal CPUE (kg/trap) series for Saint Paul Island using the GLM model detailed in the text using fishing year, fishing trip, fishing area as explanatory variables.

	Year	nCPUE	Standardised CPUE
	1980	12,4	12,3
	1981	12,4	11,9
	1982	13,6	13,0
	1983	13,7	13,8
	1984	10,6	10,8
	1985	8,1	8,7
	1986	6,6	6,3
	1987	6,0	6,2
	1988	4,7	5,0
	1989	6,2	5,8
	1990	7,8	7,2
	1991	6,8	6,6
	1992	8,4	8,1
	1993	5,9	5,8
	1994	7,1	7,8
	1995	5,5	6,9
	1996	5,1	5,6
	1997	5,7	5,6
	1998	6,8	6,5
	1999	6,8	6,5
	2000	7,9	7,9
	2001	11,3	10,6
	2002	8,2	8,0
	2003	9,6	9,2
	2004	10,1	9,9
	2005	10,0	10,3
	2006	10,4	9,6
	2007	13,6	14,6
	2008	10,4	10,2
	2009	12,5	12,1
	2010	10,5	9,6
	2011	7,4	5,9
	2012	9,6	10,5
	2013	8,2	10,0
	2014	9,7	11,0
	2015	9,6	10,8
	2016	10,1	12,4
	2017	11,6	12,1
	2018	10,5	10,8
	2019	12,0	14,2

Table 6 :

 6 Standardised CPUE and nominal CPUE (kg/trap) series for Amsterdam Island using the GLM model using fishing year, fishing trip, fishing area as explanatory variables.

	Year	nCPUE	Standardised CPUE
	1980	11,6	9,1
	1981	13,1	12,1
	1982	13,6	11,3
	1983	10,6	9,2
	1984	8,0	7,5
	1985	7,6	6,6
	1986	5,7	5,0
	1987	4,4	3,8
	1988	4,6	4,3
	1989	5,2	3,9
	1990	5,9	5,2
	1991	6,9	5,0
	1992	8,3	7,3
	1993	5,0	4,5
	1994	4,9	4,6
	1995	4,3	4,1
	1996	4,5	3,6
	1997	6,2	4,7
	1998	7,0	6,1
	1999	7,1	6,4
	2000	6,8	6,3
	2001	12,2	11,4
	2002	6,6	5,9
	2003	7,4	6,3
	2004	7,1	6,7
	2005	5,9	5,3
	2006	7,5	6,8
	2007	8,4	7,5
	2008	7,6	6,8
	2009	10,0	10,6
	2010	7,6	6,5
	2011	5,3	4,7
	2012	6,9	6,7
	2013	5,9	5,9
	2014	5,2	5,8
	2015	6,3	6,9
	2016	8,5	9,6
	2017	8,6	11,2
	2018	10,5	11,8
	2019	11,1	12,7

September 2020

TACs are also attributed to the main demersal fish exploited, cabot (Polyprion oxygeneios), rouffe antarctique (Hyperoglyphe antarctica) and saint-paul (Latris lineata).

Soaking time for individual wooden pots is comprise between

30' to 2h30 while steel pots are soaked from 12h to 17h.

All analyses have been conducted using R (R Core Team 2018) and package 'stat' for GLM.

Wald-tests.

R² = 1 -(Deviancenull_model/ Devianceselected_model)

Annex 2: Time-series of fishing effort (Number of traps, dashed line) and Catch (t, solid line) for the St. Paul and Amsterdam rock lobster. Annex 3: Mean CPUE (kg/trap) by month and fishing trip for the St. Paul and Amsterdam rock lobster. Standard deviations are represented by vertical lines. Annex 4: Time-series of rock lobster CPUE (kg/trap left axis, in red) and ocotpus CPUE (kg/trap right axis, in black) in St. Paul and Amsterdam.

Annex 5: Residual plots for Amsterdam CPUE regression analyses using fishing year, fishing trip, fishing area as explanatory variables.

Annex 6: Residual plots for Saint Paul CPUE regression analyses using fishing year, fishing trip, fishing area as explanatory variables.

Saint Paul


Stuart P Weisberg

Thomas J Connors

Yun Zhu

Matthew R Baldwin

Wen-Hsuan Lin

Sandeep Wontakal

Peter A Szabo

Steven B Wells

Pranay Dogra

Joshua Gray

Emma Idzikowski

Debora Stelitano

Francesca T Bovier

Julia Davis-Porada

Rei Matsumoto

Maya Meimei

Li Poon

Michael Chait

Cyrille Mathieu

Branka Horvat

Didier Decimo

Krystalyn E Hudson

Flavia Dei Zotti

Zachary C Bitan

Francesca La Carpia

Stephen A Ferrara

Emily Mace

Joshua Milner

Anne Moscona

Eldad Hod

Matteo Porotto

Donna L Farber

If you are citing a reference for the first time in these legends, please include all new references in the Online Methods References section, and carry on the numbering from the main References section of the paper.

Extended Data Fig. 1 Specificity of subjects' antibodies for SARS-CoV-2 S protein.

INTRODUCTION

Clinical manifestations of COVID-19 caused by the novel coronavirus SARS-CoV-2 are associated with age [START_REF] Dong | Epidemiology of COVID-19 Among Children in China[END_REF][START_REF] Wu | Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72314 Cases From the Chinese Center for Disease Control and Prevention[END_REF] . Adults develop respiratory symptoms, which can progress to Acute Respiratory Distress Syndrome (ARDS) in it most severe form, while children are largely spared from respiratory illness but can develop a life-threatening multisystem inflammatory syndrome (MIS-C) [START_REF] Cheung | Multisystem Inflammatory Syndrome Related to COVID-19 in Previously Healthy Children and Adolescents in New York City[END_REF][START_REF] Feldstein | Multisystem Inflammatory Syndrome in U.S. Children and Adolescents[END_REF][START_REF] Whittaker | Clinical Characteristics of 58 Children With a Pediatric Inflammatory Multisystem Syndrome Temporally Associated With SARS-CoV-2[END_REF] . Here, we

show distinct antibody responses in children and adults following SARS-CoV-2 infection. Adult COVID-19 cohorts had anti-Spike (S) IgG, IgM and IgA antibodies, as well as anti-Nucleocapsid (N) IgG antibody, while children with and without MIS-C had reduced breadth of anti-SARS-CoV-2-specific antibodies, predominantly generating IgG antibodies specific for the S protein but not for the N protein. Moreover, children with and without MIS-C had reduced neutralizing activity compared to both adult COVID-19 cohorts, indicating a reduced protective serological response. These results suggest a distinct infection course and immune response in children independent of whether they develop MIS-C, with implications for developing age-targeted strategies for testing and protecting the population.

Main text

The clinical manifestations of SARS-CoV-2 infection in children are distinct from adults. Children with COVID-19 rarely exhibit severe respiratory symptoms and often remain asymptomatic [START_REF] Wu | Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72314 Cases From the Chinese Center for Disease Control and Prevention[END_REF] , whereas adults experience respiratory symptoms of varying severity, and older adults and those with co-morbidities such as hypertension and diabetes have significantly higher risks of developing COVD-19-associated ARDS with high mortality [START_REF] Wu | Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72314 Cases From the Chinese Center for Disease Control and Prevention[END_REF][START_REF] Singh | Prevalence of co-morbidities and their association with mortality in patients with COVID-19: A systematic review and meta-analysis[END_REF] . In children, a rare but severe clinical manifestation of SARS-CoV-2 infection designated Multisystem Inflammatory Syndrome in Children (MIS-C), exhibits similarities to Kawasaki disease in certain inflammatory features and cardiovascular involvement while generally lacking severe respiratory symptoms [START_REF] Cheung | Multisystem Inflammatory Syndrome Related to COVID-19 in Previously Healthy Children and Adolescents in New York City[END_REF][START_REF] Feldstein | Multisystem Inflammatory Syndrome in U.S. Children and Adolescents[END_REF][START_REF] Whittaker | Clinical Characteristics of 58 Children With a Pediatric Inflammatory Multisystem Syndrome Temporally Associated With SARS-CoV-2[END_REF] . The nature of the immune response to SARS-CoV-2 in children with different clinical manifestations ranging from asymptomatic to MIS-C relative to the more common respiratory manifestations of COVID-19 in adults, remains unclear.

The generation of virus-specific antibodies which neutralize or block infectivity is the most consistent correlate of protective immunity for multiple infections and vaccines [START_REF] Lanzavecchia | Antibody-guided vaccine design: identification of protective epitopes[END_REF][START_REF] Corti | Broadly neutralizing antiviral antibodies[END_REF] . Antibodies specific for the major SARS-CoV-2 antigens, including the Spike (S) protein which binds the cellular receptor for viral entry, and the nucleocapsid (N) protein necessary for viral replication have been detected in actively infected patients and in patients with mild disease who recovered [START_REF] Wang | Neutralizing Antibodies Responses to SARS-CoV-2 in COVID-19 Inpatients and Convalescent Patients[END_REF][START_REF] Ni | Detection of SARS-CoV-2-Specific Humoral and Cellular Immunity in COVID-19 Convalescent Individuals[END_REF][START_REF] Long | Antibody responses to SARS-CoV-2 in patients with COVID-19[END_REF][START_REF] Amanat | A serological assay to detect SARS-CoV-2 seroconversion in humans[END_REF] . Anti-S antibodies, in particular, can exhibit potent neutralizing activity and are currently being pursued as a therapeutic option for infusion into patients during severe disease and for targeted generation in vaccines [START_REF] Bloch | Deployment of convalescent plasma for the prevention and treatment of COVID-19[END_REF][START_REF] Amanat | SARS-CoV-2 Vaccines: Status Report[END_REF][START_REF] Huang | A systematic review of antibody mediated immunity to coronaviruses: kinetics, correlates of protection, and association with severity[END_REF] . Defining the nature of the antibody response to SARS-CoV-2 infection as a function of age and clinical syndrome can provide essential insights for improved screening and targeted protection for the global population that continues to suffer from this relentless pandemic.

In this study, we investigated the specificity and functionality of the antibody response and its protective capacity in adult and pediatric patients seen at Columbia University Irving Medical Center/NewYork-Presbyterian (CUIMC/NYP) hospital and the Morgan Stanley Children's Hospital of New York (MSCHONY) during the height of the pandemic in New York City from March-June, 2020 [START_REF] Cheung | Multisystem Inflammatory Syndrome Related to COVID-19 in Previously Healthy Children and Adolescents in New York City[END_REF][START_REF] Bloch | Deployment of convalescent plasma for the prevention and treatment of COVID-19[END_REF][START_REF] Cummings | Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study[END_REF][START_REF] Zachariah | Clinical Features, and Disease Severity in Patients With Coronavirus Disease 2019 (COVID-19) in a Children's Hospital in New[END_REF] 1). Only 2 pediatric subjects developed respiratory failure and ARDS (Table 1; 1 with MIS-C and 1 non-MIS-C), indicating distinct inflammatory responses and clinical manifestations between children and adults in response to infection.

We quantitated SARS-CoV-2 specific antibodies for each cohort in terms of specificity and antibody class, including IgM generated initially in a primary response and IgG and IgA classes prominent in serum and secretions, respectively. Anti-S antibodies were present as IgG (Fig. 1a), IgM (Fig. 1b) and IgA (Fig. 1c) classes in adult COVID-ARDS and CPD donors, with significantly higher concentration in COVID-ARDS patients for all classes (Fig. 1a-c). By contrast, anti-S antibody titers and isotype predominance in both pediatric cohorts (MIS-C and non-MIS-C) were similar to each other and to the adult CPD subjects-showing predominant anti-S IgG (Fig. 1a), low titers of anti-S IgM (Fig. 1b) (similar to negative control pre-pandemic plasma), and variable titers of anti-S IgA antibodies (Fig. 1c). We further assessed the specificity of anti-S IgG for SARS-CoV-2 S protein compared to other coronavirus strains using a cell-based ELISA (see methods). Plasma IgG from subject samples but not pre-pandemic control samples bound SARS-CoV-2 S protein and the common circulating D614G S protein variant [START_REF] Korber | Tracking Changes in SARS-CoV-2 Spike: Evidence that D614G Increases Infectivity of the COVID-19 Virus[END_REF] , but did not significantly bind S protein from SARS-CoV-1 or MERS coronaviruses (Extended Data Fig. 1), establishing the specificity of the anti-S IgG response for SARS-CoV-2 in all cohorts. However, the abundance of IgG antibodies specific for the SARS-CoV-2 nucleocapsid (N) protein, which complexes with viral RNA and is involved in viral replication [START_REF] Cong | Nucleocapsid Protein Recruitment to Replication-Transcription Complexes Plays a Crucial Role in Coronaviral Life Cycle[END_REF] was significantly lower in both pediatric cohorts compared to the two adult cohorts (Fig. 1d). The low amounts of anti-N IgG were similar in children with and without MIS-C, and the higher anti-N IgG titers in adults were similar in the CPD and COVID-ARDS cohort, suggesting that generation of anti-N antibody is age-but not symptom-dependent.

Potential effects of age and time post-symptom onset (i.e., disease course) on the differential antibody abundance for each cohort were examined. While there was no significant correlation between anti-S IgG and age among the adult subjects and the pediatric MIS-C cohort, a modest but significant negative correlation between age and anti-S IgG titers was observed in the pediatric non-MIS-C cohort (Fig. 1e, right). Moreover, there was a significant correlation of anti-N IgG titers with subject age within the CPD group with younger adults having lower anti-N titers than older adults, while both pediatric groups had low anti-N titers across all ages (Fig. 1f). Analysis of antibody abundance as a function of time post-symptom onset revealed a significant correlation between anti-S IgG titers and increased time post-symptom for both pediatric groups and the adult COVID-ARDS group, suggestive of an evolving response over time (Fig. 2a). No correlation with symptom onset and anti-S IgM was observed (Fig. 2b). These results show that the anti-SARS-CoV-2 antibody response generated in children is predominantly anti-S IgG antibodies independent of clinical syndrome.

By contrast, adults generate broader antibody responses to infection in terms of isotypes and specificities, and exhibit increased magnitude and breadth of the anti-S antibody response with more severe disease.

The functional capacity of antibodies to provide protection correlates to their neutralizing activity in blocking virus infection.

We developed a cell-based pseudovirus assay based on a system previously reported [START_REF] Talekar | Rapid screening for entry inhibitors of highly pathogenic viruses under low-level biocontainment[END_REF][START_REF] Porotto | Simulating henipavirus multicycle replication in a screening assay leads to identification of a promising candidate for therapy[END_REF] in which multi-cycle infection of red fluorescent protein (RFP)-expressing vesicular stomatitis virus (VSV) pseudotyped with SARS-CoV-2 S protein is measured in the presence of serially diluted plasma samples (see Methods). We validated this assay by comparing neutralizing activity of plasma samples tested in the pseudovirus assay to activity measured in live virus microneutralization assay based on inhibition of cytopathic effect [START_REF] Chan | Cross-reactive antibodies in convalescent SARS patients' sera against the emerging novel human coronavirus EMC (2012) by both immunofluorescent and neutralizing antibody tests[END_REF] , and found a direct correlation in neutralizing activity calculated from the pseudovirus and live virus assay over a wide range of neutralizing activity (Fig. 3a).

Neutralizing activity as measured by the pseudovirus assay showed differences between the four cohorts that were associated with age group and/or clinical severity. The pediatric MIS-C and Non-MIS-C groups both exhibited significantly lower neutralizing activity than the adult CPD and COVID-ARDS groups, while plasma from COVID-ARDS patients show the highest neutralizing potency of the four groups across the dilution series (Fig. 3b,c). No differences were observed in neutralizing activity in the MIS-C compared to the pediatric Non-MIS-C group (Fig. 3b,c). Only a small fraction of antibodies raised against viral antigens will have neutralizing activity against the virus, which correlates with protective capacity [START_REF] Gao | Development of an inactivated vaccine candidate for SARS-CoV-2[END_REF] . By linear regression, there was significant correlation between the abundance of anti-S IgG and neutralizing activity within the CPD, MIS-C and pediatric Non-MIS-C groups, albeit with a significantly lower elevation and y-intercept for MIS-C group relative to the COVID-ARDS and CPD groups (Fig. 3d).

Together, these results establish a significant quantitative difference in neutralizing activity of anti-SARS-CoV-2 antibodies between pediatric and adult groups.

We examined potential effects of age and disease course on neutralizing activity in the different groups. There was no correlation between neutralizing activity and patient age in either adult group (Fig. 3d). However, there was a significant decline of neutralizing activity with patient age in the pediatric Non-MIS-C group (Fig. 3e, right) similar to the decrease in anti-S IgG abundance with age observed during the teenage years (Fig. 1e, right). Neutralizing activity within each group did not correlate with time postsymptom onset except in the severely ill COVD-ARDS group (Fig. 4a). Moreover, MIS-C patients also maintained the same titers of anti-S IgG and neutralizing activity 2-4 weeks after hospital discharge based on paired analysis of the follow-up compared to the retested primary sample in 10/16 (62.5%) of the patients (Fig. 4b). Together, these results indicate that lower magnitude of functional antibody responses in pediatric SARS-CoV-2 infection compared to adults is age associated and not related to infection course.

To better define how SARS-CoV-2 antibody responses are related to age and clinical syndrome, we performed multivariable linear regression analysis to control for effects of demographic and clinical covariates. Consistent with the grouped analysis (Fig. 1a-d, 3b), analysis of all pediatric and adult data showed that the pediatric age group is a significant predictor of lower SARS-CoV-2 neutralizing activity, anti-S IgM and anti-N IgG, and these relationships are independent of time post-symptom onset, clinical syndrome or sex (Supplementary Table 3). In addition, ARDS was found to be a significant independent predictor of higher SARS-CoV-2 neutralizing activity, anti-S IgG and anti-S IgM (Supplementary Table 3). Within the subgroup of pediatric subjects, age was found to be a significant independent predictor of SARS-CoV-2 neutralizing activity (Supplementary Table 3), consistent with the pairwise analysis (Fig. 3e, right). These results show that the observed relationships of age and clinical syndrome with SARS-CoV-2 antibody responses are independent of potentially confounding factors, including being male.

Together, our results show quantitative and qualitative differences in the anti-SARS-CoV-2-specific antibody response across the spectrum of infection in children compared to adults. Children exhibited a SARS-CoV-2-specific antibody response that was largely limited to IgG anti-S antibodies with the lowest overall level of neutralizing activity compared to adult COVID-19 cohorts. In addition, children with different disease severities (i.e. with or without MIS-C) exhibited similar antibody profiles, while in the adult cohorts, those with the most severe disease (ARDS) had higher abundance, breadth and neutralizing activity of anti-SARS-CoV-2 antibodies compared to adults who recovered from mild disease. While there was an association with increased amounts of anti-S IgG and time post-symptom onset, age remained the major factor distinguishing antibody profiles. Additionally, the durable responses seen in follow-up samples from MIS-C subjects provide evidence for relative stability of antibody abundance over a period of weeks. These findings suggest distinct primary SARS-CoV-2 infection courses and immune responses in children and adults.

Optimal protection to viral respiratory tract infections is mediated by virus-specific immunological memory developed during previous exposures [START_REF] Kohlmeier | Immunity to respiratory viruses[END_REF] . The majority of primary exposures, especially to viral respiratory pathogens which are ubiquitous in the population, occur during infancy and childhood and virus-specific memory is established by adult life [START_REF] He | Analysis of the frequencies and of the memory T cell phenotypes of human CD8+ T cells specific for influenza A viruses[END_REF][START_REF] Prabhudas | Challenges in infant immunity: implications for responses to infection and vaccines[END_REF] . Consequently, it is largely unknown how primary immune responses to viral pathogens may differ between children and adults. The sudden and widespread emergence of SARS-CoV-2 as a novel pathogen enables the study of primary immune responses across all ages. The reduced respiratory symptoms and low incidence of ARDS in the pediatric population [START_REF] Wu | Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72314 Cases From the Chinese Center for Disease Control and Prevention[END_REF] suggest a distinct infection course, possibly due to lower expression of the viral receptor (ACE2) in pediatric airway epithelial cells [START_REF] Bunyavanich | Nasal Gene Expression of Angiotensin-Converting Enzyme 2 in Children and Adults[END_REF] or a more robust innate immune response in children [START_REF] Pierce | Immune responses to SARS-CoV-2 infection in hospitalized pediatric and adult patients[END_REF][START_REF] Gruber | Mapping Systemic Inflammation and Antibody Responses in Multisystem Inflammatory Syndrome in Children (MIS-C)[END_REF][START_REF] Consiglio | The Immunology of Multisystem Inflammatory Syndrome in Children with COVID-19[END_REF] . A milder infection course in pediatric groups is further consistent with lower abundance of anti-N-specific antibodies identified here, as release of N proteins requires lysis of virally infected cells. The age association of anti-N antibodies in the adult CPD group is consistent with the age-associated risk for more severe and prolonged disease from SARS-CoV-2 infection. While current platforms to determine prior infection with SARS-CoV-2 rely heavily on the detection of anti-N IgG, our results suggest that these testing platforms may have decreased sensitivity for assessing previous infections among the pediatric population.

The reduced functional antibody response in children compared to adults could also be due to efficacious immune-mediated viral clearance resulting in fewer respiratory symptoms and severe illness. The presence of SARS-CoV-2-specific T cells in the peripheral blood of recovered and COVID-ARDS adults has been demonstrated in multiple cohorts [START_REF] Weiskopf | Phenotype and kinetics of SARS-CoV-2-specific T cells in COVID-19 patients with acute respiratory distress syndrome[END_REF][START_REF] Grifoni | Targets of T Cell Responses to SARS-CoV-2 Coronavirus in Humans with COVID-19 Disease and Unexposed Individuals[END_REF][START_REF] Sekine | Robust T Cell Immunity in Convalescent Individuals with Asymptomatic or Mild COVID-19[END_REF] , though the protective capacity of these T cells is unclear. The pediatric T cell response to SARS-CoV-2 requires investigation but may exceed the adult responses due to an increased number of naïve T cells available to respond to new pathogens [START_REF] Kumar | Human T Cell Development, Localization, and Function throughout Life[END_REF] , or more recently acquired T cell memory to related coronavirus strains [START_REF] Mateus | Selective and cross-reactive SARS-CoV-2 T cell epitopes in unexposed humans[END_REF] due to children experiencing more respiratory illnesses. The IgG predominance in the majority of children examined here is consistent with pre-existing immunological memory. Interestingly, less severe manifestations of COVID-19 have been associated with a more coordinated adaptive immune responses in adults [START_REF] Moderbacher | Antigen-Specific Adaptive Immunity to SARS-CoV-2 in Acute COVID-19 and Associations with Age and Disease Severity[END_REF] , suggesting that the quality and quantity of the immune response is important for protection from severe disease, which are important future areas of investigation for understanding the immune response to SARS-CoV-2 infection in children.

The similar antibody profiles in children with and without MIS-C suggests that the adaptive immune response per se, is not associated with MIS-C pathogenesis. However, reduced neutralizing activity may predispose children to develop low-level, persistent infection in other sites resulting in MIS-C. Children can present with gastrointestinal symptoms rather than respiratory illness and demonstrate prolonged fecal shedding of the virus [START_REF] Xu | Characteristics of pediatric SARS-CoV-2 infection and potential evidence for persistent fecal viral shedding[END_REF] . Alternately, the presence of non-neutralizing anti-S Abs could lead to antibodydependent enhancement of infection (ADE) known to occur in viral infections including SARS-CoV-1 [START_REF] Iwasaki | The potential danger of suboptimal antibody responses in COVID-19[END_REF] . Additionally, autoreactive antibodies recently identified in children with MIS-C may promote aberrant immune responses leading to systemic inflammation [START_REF] Gruber | Mapping Systemic Inflammation and Antibody Responses in Multisystem Inflammatory Syndrome in Children (MIS-C)[END_REF][START_REF] Consiglio | The Immunology of Multisystem Inflammatory Syndrome in Children with COVID-19[END_REF] .

Further studies delineating the differences in adult and pediatric immune responses to SARS-CoV-2 are warranted to define how protection or pathology is mediated in response to this pathogen. In summary, our results suggest a distinct infection course and immune response in children independent of whether they develop MIS-C, with implications for developing age-targeted strategies for testing and protecting the population. Identical, five-fold serial dilutions were performed for all samples and there were no missing titration data points for any of the samples.

SARS-CoV-2 viral stock production

SARS-CoV-2 (2019-nCoV/USA_WA1/2020) was kindly provided to B.H. by World Reference Center for Emerging Viruses and Arboviruses (WRCEVA). To generate virus stocks, Vero E6 cells (kindly provided by F. Cosset, CIRI -International Center for Infectiology Research, Inserm) were inoculated with virus at a MOI of 0.01. The virus-containing medium was harvested at 72 h post infection, clarified by low-speed centrifugation, aliquoted, and stored at -80°C. Virus stock was quantified by limiting dilution plaque assay on Vero E6 cells as described [START_REF] Guillaume | Nipah virus: vaccination and passive protection studies in a hamster model[END_REF][START_REF] Mathieu | Nipah virus uses leukocytes for efficient dissemination within a host[END_REF] .

Live virus neutralization assay

Two-fold dilutions of plasma in 50 μL of Dulbecco`s Modified Eagle Media (DMEM) were incubated with 200 plaque forming units (PFU) of SARS-CoV-2 in 50 μL of DMEM for 30 min at 4 °C. 100 μL of DMEM 4%FBS containing 4 × 10 4 Vero E6 cells were added on the top of the former mix in order to have final dilution of sera from 1:50 to 1:6400 (4 wells per dilution). Cells were then incubated for 3 days at 37 °C, 5% CO 2 . Cytopathic effect was revealed by crystal violet staining, and scored by an observer blinded to the study design and sample identity. Neutralization end point titers were expressed as the value of the last serum dilution that completely inhibited virus-induced cytopathic effect.

Quantitation of antibody titrations in ELISA and neutralization assays

For quantitation of neutralization titers in the pseudovirus assay, RFP signal driven by the pseudovirus normalized to the GFP signal derived from the SARS-Cov-2 S protein and ACE2 transfected cells was measured at 24 and 48 h; the ratio of normalized RFP at 48 h (RFP48) to normalized RFP at 24 h (RFP24) was calculated. This ratio provides a read-out of multicycle infection of the S protein/ACE2 transfected cell monolayer by S protein-bearing pseudoviruses. Neutralizing activity for each sample was calculated by taking the sum of the reciprocal of the RFP48/RFP24 ratio at all 6 plasma dilutions for each sample as described [START_REF] Hartman | Absorbance summation: A novel approach for analyzing high-throughput ELISA data in the absence of a standard[END_REF] , and also by percent inhibition of multicycle replication at each dilution calculated based on the RFP48/RFP24 ratio of the sample, control wells of maximal multicycle replication without inhibition (MAX) and control wells with 100% inhibition of multicycle replication using a lipidated SARS-CoV-2 derived peptide (MIN) [START_REF] Pessi | A general strategy to endow natural fusion-protein-derived peptides with potent antiviral activity[END_REF][START_REF] Xia | Fusion mechanism of 2019-nCoV and fusion inhibitors targeting HR1 domain in spike protein[END_REF] . The equation for % inhibition of multicycle replication: 100 × (1-(sample-MAX)/( MAX -MIN)).

Statistical analysis

All statistical analysis was performed using Prism software version 8.4.3 (GraphPad). Comparisons of clinical data between groups was performed using the Mann-Whitney U test and one-way Analysis of Variance (ANOVA) and Dunn's multiple comparisons test. Comparisons of antibody levels and neutralization activity were performed using one-way ANOVA and Tukey's multiple comparisons test.

Pairwise correlation analysis was performed using simple linear regression. Multiple linear regression analysis was performed on the combined adult and pediatric data as well as the adult and pediatric cohorts individually. For all analyses, outcome variables included the abundance of anti-S IgG, anti-S IgM, anti-N IgG and SARS-CoV-2 neutralizing activity. For the combined adult and pediatric dataset, the independent variable is pediatric age group ('Pediatric') and covariates include sex, clinical syndrome and time post symptom onset (days). For the adult and pediatric subgroup analyses, the independent variables are clinical syndrome and age (years), and covariates include sex and time post symptom onset (days). For each variable, P values were calculated using the t statistic with two-sided hypothesis testing.

  Figure # Figure titleOne sentence only

  The specificity of antibodies for SARS-CoV-2 S protein compared to SARS-CoV-1 and MERS S protein was assayed in a cell-based IgG binding assay. HEK293T cells were transfected with S protein and its common variants from the indicated coronaviruses. The transfected cells were then incubated with human plasma from the indicated study groups and bound human IgG was detected using fluorescently tagged protein G (see methods). Shown are the percentage of the S protein transfected cells that are positive for human IgG in each patient group: CPD, black squares, n=19; COVID-ARDS, red squares, n=13; pediatric non-MIS-C, n=28; MIS-C, green circles, n=16; and control plasma from prepandemic donors (grey triangles; Neg, n=6). Black bar indicates the median+interquartile range. P values were calculated by one-way ANOVA with Dunnett's multiple comparisons test (CPD, SARS-CoV-2 vs. SARS-CoV-1: P=0, SARS-CoV-2 vs. MERS: P=0; COVID-ARDS, SARS-CoV-2 vs. SARS-CoV-1: P=0, SARS-CoV-2 vs. MERS: P=0; Ped non-MIS-C, SARS-CoV-2 vs. SARS-

Figure 1 . 19 .

 119 Figure 1. Children with and without MIS-C exhibit distinct SARS-CoV-2 antibody profiles compared to adults with COVID-19. Levels of antibodies to SARS-CoV-2 spike (S) and nucleocapsid (N) proteins were measured using serial dilutions of patient plasma in an indirect ELISA assay to detect anti-S IgG (a), anti-S IgM (b), anti-S Ig A (c) and anti-N IgG (d). Shown is the absorbance sum across 6 serial 1:4 plasma dilutions from adult convalescent plasma donors (CPD, open black squares, n=19); adult patients with COVID-19 induced acute respiratory distress syndrome (COVID-ARDS, closed red squares, n=13); pediatric patients with a history of SARS-CoV-2 infection but not MIS-C (Non-MIS-C, open blue circles, n=31); patients with MIS-C (MIS-C, closed green circles, n=16); and control plasma from pre-pandemic donors (Neg, grey triangles, n=10). Black bar indicates the median+interquartile range. P values were calculated by one-way ANOVA with Sidak's multiple comparisons test. Anti-S IgG (a), CPD vs. COVID ARDS: P=1.32x10 -4 , CPD vs. Ped non-MIS-C: P=0.59, COVID ARDS vs. MIS-C: P=8.53x10 -6 , Ped non-MIS-C vs. MIS-C: P=0.24. Anti-S IgM (b), CPD vs. COVID ARDS: P=6.93x10 -5 , CPD vs. Ped non-MIS-C: P=0.33, COVID ARDS vs. MIS-C: P=2.54x10 -6 , Ped non-MIS-C vs. MIS-C: P=0.99. Anti-S IgA (c), CPD vs. COVID ARDS: P=3.82x10 -7 , CPD vs. Ped non-MIS-C: P=0.08, COVID ARDS vs. MIS-C: P=9.06x10 -7 , Ped non-MIS-C vs. MIS-C: P=0.11. Anti-N IgG (d), CPD vs. COVID ARDS: P=0.93, CPD vs. Ped non-MIS-C: P=3.31x10 -5 , COVID ARDS vs. MIS-C: P=3.88x10 -5 , Ped non-MIS-C vs. MIS-C: P=0.99.Significance is indicated as *P < 0.05, **P < 0.01, ***P < 0.001 or P>0.05 (ns). For anti-S IgG (e) and anti-N IgG (f), subject antibody levels are also plotted against patient age within the adult (left) and pediatric cohorts (right) with the best fit lines and P values calculated using simple linear regression. Anti-S IgG vs. Age (Ped non-MIS-C: R2=0.23, slope=-0.077, y-int=2.70). Anti-N IgG vs. Age (CPD: R2=0.34, slope=0.023, y-int=0.12).

Figure 2 .

 2 Figure 2. Relationship of anti-S IgG and IgM levels with time post symptom onset for pediatric and adult cohorts. Levels of anti-S IgG (a), and IgM (b) were plotted against the time post symptom onset for those subjects that were symptomatic either with COVID-19 or MIS-C. The adult groups, CPD (open black squares, n=19) and COVID-ARDS closed red squares, n=13) are plotted on the left and the pediatric groups, MIS-C (closed green circles, n=16) and non-MIS-C (open blue circles, n=16) are plotted on the right with the best fit line and P value, reported to 4 decimal places, was calculated using simple linear regression. Anti-S IgG vs. Time post

Figure 3 .

 3 Figure 3. Reduced SARS-CoV-2 neutralizing activity in children with and without MIS-C compared to adults with mild and severe COVID-19. a, Plasma neutralizing activity in the pseudovirus assay was correlated with the end point titers in a live virus microneutralization assay based on inhibition of cytopathic effect (n=13, see methods). b, Neutralizing activity for SARS-CoV-2specific antibodies was determined using the pseudovirus assay (see methods). Neutralizing activity is shown from adult convalescent plasma donors (CPD, open black squares, n=19); adult patients with COVID-19 induced acute respiratory distress syndrome (COVID-ARDS, closed red squares, n=13); pediatric patients with a history of SARS-CoV-2 infection but not MIS-C (Non-MIS-C, open blue circles, n=31); patients with MIS-C (MIS-C, closed green circles, n=16); and control plasma from pre-pandemic donors (Neg, grey triangles, n=10). Black bar indicates the median+interquartile range. The P values were calculated by one-way ANOVA with Sidak's multiple comparisons test (CPD vs. COVID ARDS: P=0.019, CPD vs. Ped non-MIS-C: P=0.0031, COVID ARDS vs. MIS-C: P=3.35x10 -6 , Ped non-MIS-C vs. MIS-C: P=1.0). Significance is indicated as *P < 0.05, **P < 0.01, ***P < 0.001 or P>0.05 (ns). Shown (c) are the percent inhibition values of S-protein mediated pseudoviral replication plotted against the plasma dilution factors for all subjects in each group. Neutralizing activity is plotted against anti-S IgG levels (d) and patient age (e) within the adult (left) and pediatric cohorts (right). The best fit lines and P values (reported to 4 decimal places), were calculated using simple linear regression. Neutralizing activity vs. anti-S IgG (CPD: R2=0.29, slope=0.36, y-int=0.88; MIS-C: R2=0.51, slope=0.38, y-int=0.43; Ped non-MIS-C: R2=0.21, slope=0.22, y-int=0.86). Neutralizing activity vs. age (Ped non-MIS-C: R2=0.20, slope=-0.034, y-int=1.64).

Figure 4 .

 4 Figure 4. Relationship of anti-SARS-CoV-2 neutralizing activity with time post symptom onset. a, Levels of neutralization activity were plotted against the time post symptom onset for those subjects that were symptomatic either with COVID-19 or MIS-C. The adult groups, CPD (open black squares, n=19) and COVID-ARDS closed red squares, n=13) are plotted on the left and the pediatric groups, MIS-C (closed green circles, n=16) and non-MIS-C (open blue circles, n=16) are plotted on the right with the best fit line and P value calculated using simple linear regression (COVID-ARDS: R2=0.36, slope=0.040, y-int=1.34). b, The anti-S IgG levels (left) and neutralizing activity (right) of MIS-C subjects (n=10) during the acute phase of illness and at a follow-up visit 2-4 weeks after hospital discharge. The P values were calculated by two way paired t-test.

  ) e Pediatric and Adult specific scoring applied to groups; not meant for direct comparison f Day of admission for MIS-C, day of intubation for COVID-ARDS, day of PCR or Serology sample testing for Non MIS-C g 30 Day In-hospital mortality, 4 patients remain hospitalized h Values above upper limit entered as; D-Dimer (20 mg/mL), Ferritin (100,000 ng/mL), CRP (200 mg/L), Interleukin-6 (315 pg/mL), Lactate Dehydrogenase (5000 U/L) i Statistical testing for Absolute Neutrophil Count, Absolute Lymphocyte Count and Albumin done via Kruskal-Wallis one-way analysis of variance. Statistical testing for all other laboratory results done by two-tailed Mann-Whitney test. P values were calculated to 4 decimal places. Absolute Neutrophil Count and Absolute Lymphocyte Count; n=13 COVID-ARDS, n=16 MIS-C, n=27 Non MIS-C. Albumin; n=13 COVID-ARDS, n=16 MIS-C, n=15 Non MIS-C. D-dimer and Ferritin; n=13 COVID-ARDS, n=16 MIS-C. For High Sensitivity CRP; n=12 COVID-ARDS, n=16 MIS-C. Interleukin-6 and Troponin; n=11 COVID-ARDS, n=16 MIS-C. Lactate Dehydrogenase; n=12 COVID-ARDS, n=15 MIS-C. Procalcitonin; n= 13 COVID-ARDS, n=12 MIS-C. then combined with diluted serum or plasma in 96-well plates. During the assay, infected S proteinexpressing HEK293T cells generate VSV-ΔG-RFP viruses that bear S protein which subsequently infects and drives RFP expression in Vero cells and undergo multiple cycles of entry and budding in the HEK293T cells due to the co-expression of S protein with ACE2. The GFP and RFP signals are measured 24-48 h after plating (Infinite M1000 PRO microplate reader, Tecan), resulting in robust amplification of the S protein pseudovirus-driven RFP signal between 24-48 h. Inhibition of RFP signal amplification indicates S protein neutralizing activity in patient plasma (Extended Data Fig. 1).

  Figure 1

  Figure 2

Figure 3 a

 3 Figure 3

  ). Subjects were diagnosed as infected with SARS-CoV-2 based on history of symptoms, PCR-positive test for virus and/or by serology (Table1

Table 1 . Demographic and Clinical Data

 1

			Adults	Pediatric
		CPD	COVID-ARDS	MIS-C	Non MIS-C
		(n=19)	(n=13)	(n=16)	(n=31)	P Value
	Demographics
	Age, years, median (range)	45 (28-69)	62 (19-84)	11 (4-17)	11 (3-18)
	Sex, male (%)	10 (53%)	11 (85%)	7 (44%)	17 (55%)
	Body Mass Index, median (IQR)	na	33.8 (28.4-36.1) 19.1 (17.3-25.5) 19.3 (16.9-22.3)
	Race or Ethnic Group (%) a
	Hispanic or Latino	1 (5%)	4 (31%)	4 (25%)	13 (42%)
	Black or African American	0	3 (23%)	7 (44%)	4 (13%)
	White	10 (53%)	2 (15%)	7 (44%)	15 (48%)
	Asian	6 (32%)	0	0	0
	Pacific Islander	2 (11%)	0	0	0
	Other or Unknown	1 (5%)	5 (38%)	1 (6%)	7 (23%)
	Clinical Characteristics
	SARS-CoV-2 PCR Positive (%) b	na	13 (100%)	8 (50%)	22 (71%)
	Asymptomatic (%)	na	0	0	15 (48%)
	Days Post Symptom Onset, median (IQR) c	24 (19-37)	16 (14-21)	6 (4-7)	29 (17-44) d
	SOFA Score e , median (IQR) f	na	11 (9.5-14)	4 (3-7)	na
	Acute Respiratory Distress Syndrome (%)	na	13 (100%)	1 (6%)	1 (3%)
	In-hospital Mortality (%) g	na	6 (46%)	0 (0%)	0 (0%)
	Laboratory Results, median (IQR) f,h,i
	Absolute Neutrophil Count, x10(3)/μL	na	14.7 (9.1-25.2)	8.9 (7.2-16.4)	5.0 (3.2-8.0)	0.0005
	Absolute Lymphocyte Count x10(3)/μL	na	0.9 (0.7-1.4)	0.8 (0.4-1.5)	2.0 (1.3-2.8)	0.0001
	Albumin, g/dL	na	3.

  CPD, convalescent plasma donor; ARDS, Acute Respiratory Distress Syndrome; MIS-C Multisystem Inflammatory Syndrome in Children; SOFA, Sequential Organ Failure Assessment; IQR, Interquartile Range; PCR, Polymerase chain reaction; CRP, C-Reactive Protein a Individuals included in all groups for which they identified b Indeterminate tests were treated as positive c Respiratory symptoms/COVID-19 symptoms for CPD/ARDS groups and symptoms of MIS-C for MIS-C group d Subjective reporting of days post symptom onset for those presenting with symptoms or total days after confirmed COVID-19 exposure (reportable data available for n=16 subjects

	-dimer, μg/mL	na	7.9 (1.7-16.1)	3.1 (1.7-4.3)	na	0.07
	Ferritin, ng/mL	na	1933 (971-2693)	521 (298-998)	na	0.002
	High Sensitivity CRP, mg/L	na	128 (69-207)	214 (47-300)	na	0.56
	Interleukin-6, pg/mL	na	82 (56-315)	219 (54-315)	na	0.63
	Lactate Dehydrogenase, U/L	na	777 (638-1379)	268 (229-373)	na	0.0003
	Procalcitonin, ng/mL	na	0.4 (0.3-2.0	8.8 (2.1-61.6)	na	0.002
	Troponin T, high sensitivity, ng/L	na	24 (16-59)	20 (6-92)	na	0.85
	Abbreviations:

ACKNOWLEDGEMENTS

We thank F. Cosset for the donation of Vero E6 cells. We wish to express our gratitude to the Medical ICU nurse champions, C. Garcellano, T. Drukdak, H. Avila Raymundo, L. Wagner, and R. Lee, who led the efforts to obtain patient samples for the adult ARDS patients, to E. Hernandez and L. Gomez for their roles as clinical coordinators, and to the nurses and clinical staff in the Pediatric Intensive Care Unit of MSCHONY. We acknowledge the dedication, commitment, and sacrifice of the other nurses, providers, and personnel who helped care for these patients during the COVID-19 crisis. We acknowledge the suffering and loss of our COVID-19 patients and of their families and our community.

Funding/Support

This work was supported by NIH grants AI128949, AI100119, AI106697 awarded to D.L.F., NIH grants AI121349, NS091263, NS105699, and AI146980 awarded to M.P., and AI114736 awarded to A.M. S.W. is supported by NIH K08DK122130; T.J.C. is supported by NIH K23 AI141686.

Role of the Funder:

The funders/sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data availability statement

The raw data analyzed for this study are provided as Source Data. Additional supporting data are available from the authors upon request.

Code availability statement

N/A

AUTHOR CONTRIBUTIONS

All authors meet authorship criteria and approve of publication. S.P.W., T.J.C., M.P. and D.L.F., A.M., and E.H. conceived and designed the study and assays, wrote and/or edited the paper. T.J.C., M.R.B., D.L.F., E.M., J.M., E.I., coordinated sample acquisition, recruited and consented MIS-C and COVID-ARDS patients. T.J.C., J.D-P., S.P.W., E.M., J.M. and M.R.

Competing Interests statement

The authors have no conflicts with regard to this work.

METHODS

Subjects

We recruited a total of 79 subjects from MSCHONY and CUIMC/NYP who represented distinct clinical manifestations of SARS-CoV-2 infection and different age groups divided into four cohorts: 1. PCR from nasopharyngeal swabs or antibody positive serology. ARDS was defined by clinical consensus criteria; including infiltrates on chest radiograph and a PaO2/FiO2 ratio of less than 300, or pediatric criteria equivalent [START_REF] Ranieri | Acute respiratory distress syndrome: the Berlin Definition[END_REF][START_REF] Khemani | Pediatric acute respiratory distress syndrome: definition, incidence, and epidemiology: proceedings from the Pediatric Acute Lung Injury Consensus Conference[END_REF] . MIS-C was defined using the Center for Disease Control definition; <21 years of age, fever >38°C for >24 h, laboratory evidence of inflammation, hospital admission, multisystem involvement, no alternative plausible diagnosis, and positive SARS-Cov-2 serology [START_REF] Cdc | Multisystem Inflammatory Syndrome in Children (MIS-C) Associated with Coronavirus Disease 2019 (COVID-19)[END_REF] .

Sequential Organ Failure Assessment (SOFA) scores were calculated on all hospitalized subjects using previously validated adult and pediatric score tools to provide additional clinical insight into subject disease severity [START_REF] Singer | The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3)[END_REF][START_REF] Matics | Adaptation and Validation of a Pediatric Sequential Organ Failure Assessment Score and Evaluation of the Sepsis-3 Definitions in Critically Ill Children[END_REF][START_REF] Vasilevskis | Validity of a Modified Sequential Organ Failure Assessment Score Using the Richmond Agitation-Sedation Scale[END_REF] . This study was approved by the Institutional Review Board at CUIMC. Written consent was obtained from CPD subjects. Due to the limitations placed on direct contact with infected subjects and a need to conserve personal protective equipment, verbal informed consent was obtained from surrogates of critically ill COVID-ARDS subjects and verbal parental consent was obtained for MIS-C subjects. Biospecimens and data from Non-MIS-C pediatric patients were obtained from the Columbia University Biobank (CUB).

Sample Processing

Blood samples were obtained at time of outpatient donation for CPD subjects, at time of admission for MIS-C subjects, during clinical care for pediatric Non-MIS-C subjects and following diagnosis of ARDS for COVID-ARDS patients. Plasma was isolated from whole blood via centrifugation. Aliquots were frozen at -80˚C prior to analysis.

Purification of SARS-CoV-2 viral proteins

The ectodomain of the SARS-CoV-2 spike trimer [START_REF] Wrapp | Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation[END_REF] was cloned into mammalian expression vector pCAGGS (Addgene), with a fold-on tag followed by 6xHis tag and Strep tag II at the C-terminal. This expression vector was transiently transfected into HEK293F cells and the spike trimer secreted in the supernatant was purified 3-5 days post transfection by metal-affinity chromatography using an Ni-NTA (Qiagen) column. SARS-CoV-2 nucleocapsid protein (N) was cloned into pET28a(+) vector (Millipore-Sigma) with an AAALE linker and 6xHis tag at the C-terminal. The NP construct was then used to transform into Escherichia coli BL21 (DE3) pLysS cells and the target protein was produced and purified from the bacterial lysate by metal affinity chromatography using an Ni-NTA (Qiagen) column, followed by size-exclusion chromatography on a Superdex 200 10/300 GL column.

Enzyme-linked immunosorbent assay (ELISA) for detection of virus-specific antibodies

SARS-CoV-2 spike trimer and N were coated on 96-well ELISA plates at 4 overnight, and unbound proteins were then removed washing with PBS, following by blocking with PBS/3% non-fat dry milk.

Plasma samples were serially diluted in PBST (0.1% Tween-20 in PBS) + 10% bovine calf serum starting with 1:100, and five successive four-fold dilutions into each well of the coated plate which was incubated at 37 for 1 h, followed by washing 6 times with PBST. Peroxidase affiniPure goat antihuman IgG (H+L) antibody (1:3,000 dilution), anti-human IgM antibody (1:10,000 dilution) (Jackson Immune Research), or anti-human IgA antibody (1:5,000 dilution) (Thermofisher) was subsequently added into each well and incubated for 1 h at 37 , washed and Tetramethylbenzidine substrate (Sigma) was added and the reaction was stopped using 1 M sulfuric acid. Absorbance was measured at 450 nm and expressed as an optical density, or OD 450 value. Identical serial dilutions were performed for all samples with no missing titrations.

Pseudovirus neutralization assay

We adapted a pseudovirus-based neutralization strategy we previously developed to measure inhibition of infection by high biocontainment enveloped viruses in a large number of samples under low-level biocontainment [START_REF] Talekar | Rapid screening for entry inhibitors of highly pathogenic viruses under low-level biocontainment[END_REF][START_REF] Porotto | Simulating henipavirus multicycle replication in a screening assay leads to identification of a promising candidate for therapy[END_REF] . For this assay, SARS-CoV-2 S protein is pseudotyped onto recombinant vesicular stomatitis virus (VSV) that expresses red fluorescent protein (RFP) but does not express the VSV attachment protein, G (VSV-ΔG-RFP). Initially, VSV-ΔG-RFP pseudotyped with VSV G is used to infect 293T (human kidney epithelial) cells that were co-transfected with full-length codon optimized SARS-CoV-2 S-protein (Epoch Life Science), the viral entry receptor ACE2 (Epoch Life Science) and green-fluorescent protein (GFP). Infected HEK293T cells are then mixed at a 2 to 1 ratio with Vero (African green monkey kidney) cells, which have high endogenous expression of ACE2 [START_REF] Hoffmann | SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor[END_REF] . The cells are