Vera Afreixo

Carlos A C Bastos

Armando J Pinho

Sara P Garcia

Paulo J S G Ferreira

Genome analysis with distance to the nearest dissimilar nucleotide

Keywords: alignment-free genome comparison, inter-nucleotide distances, nearest dissimilar distances, DNA sequences

DNA may be represented by sequences of four symbols, but it is often useful to convert those symbols into real or complex numbers for further analysis.

Several mapping schemes have been used in the past, but most of them seem to be unrelated to any intrinsic characteristic of DNA. The objective of this work was to study a mapping scheme that is directly related to DNA characteristics, and that could be useful in discriminating between different species.

Recently, we have proposed a methodology based on the inter-nucleotide distance, which proved to contribute to the discrimination among species. In this paper, we introduce a new distance, the distance to the nearest dissimilar nucleotide, which is the distance of a nucleotide to first occurrence of a different nucleotide. This distance is related to the repetition structure of single nucleotides. Using the information resulting from the concatenation of the distance to the nearest dissimilar and the inter-nucleotide distance, we found that this new distance brings additional discriminative capabilities.

Introduction

DNA sequences have been converted to numerical signals using different mappings. A commonly used mapping is to consider binary sequences that describe the position of each symbol (Voss, 1992). The binary representation is certainly one of the earliest and one of most popular mappings of DNA.

However, several other different mappings have been proposed (see for example, [START_REF] Silverman | A measure of DNA periodicity[END_REF]; [START_REF] Jeffrey | Chaos game representation of gene structure[END_REF]; Zhang and Zhang (1994); [START_REF] Buldyrev | Long-range correlation properties of coding and noncoding DNA sequences: GenBank analysis[END_REF]; [START_REF] Anastassiou | Genomic signal processing[END_REF]; [START_REF] Cristea | Large scale features in DNA genomic signals[END_REF]; [START_REF] Ning | Preliminary wavelet analysis of genomic sequences[END_REF]; [START_REF] Brodzik | Symbol-balanced quaternionic periodicity transform for latent pattern detection in DNA sequences[END_REF]; [START_REF] Liao | Application of 2-d graphical representation of DNA sequence[END_REF]; [START_REF] Akhtar | On DNA numerical representation for period-3 based exon prediction[END_REF]; Randic (2008); [START_REF] Nair | Visualization of genomic data using inter-nucleotide distance signals[END_REF]; [START_REF] Afreixo | Genome analysis with inter-nucleotide distances[END_REF]). Some of the mappings used in DNA processing do not have a simple numerical interpretation and others do not have biological motivation. Also, some of the representations are not reversible and do not take into account the sequence structure. Currently, there is no ideal mapping to analyze every type of correlation in DNA sequences.

In a previous work, we explored the inter-nucleotide (IN) distance, the distance to the first occurrence of the same symbol, to perform a comparative analysis between species [START_REF] Afreixo | Genome analysis with inter-nucleotide distances[END_REF]. In this work, we present a new DNA numerical profile and a new mapping to explore the correlation structure of DNA: the distance to the nearest dissimilar (ND) nucleotide. This representation converts any DNA sequence into a unique numerical sequence with lower length, where each number represents the distance of a symbol to the next occurrence of a different symbol. We introduced also four sequences, one for each nucleotide, to represent the ND distances. This allows to perform comparative analysis between the behavior of the four nucleotides distance sequences and the global sequence.

From the perspective of molecular evolution, DNA sequences may reflect both the results of random mutation and selective evolution. One should subtract the random background from the simple counting result in order to highlight the contribution of selective evolution [START_REF] Qi | Whole proteome prokaryote phylogeny without sequence alignment: A K-string composition approach[END_REF][START_REF] Ding | A simple feature representation vector for phylogenetic analysis of DNA sequences[END_REF]. Therefore, we present an analysis of the relative error to highlight the contribution of selective evolution of the DNA of each species. This residual analysis may be used, for example, to perform multiple organism comparisons.

Phylogenetic trees reproduce the evolutionary tree that represents the historical relationships between the species. Recent phylogenetic tree algorithms use nucleotide sequences. Typically, these trees are constructed with multiple sequence alignment [START_REF] Hodge | A myosin family tree[END_REF], which is a computationally demanding task. Recently, alignment-free methods have been proposed and present some advantages over multiple sequences alignment methods (see for example [START_REF] Sims | Whole-genome phylogeny of mammals: evolutionary information in genic and nongenic regions[END_REF]; Vinga and Almeida (2003)).

The distance that we address in this paper seems to possess discriminating properties that might be helpful in inferring phylogenies. We do believe that this claim is supported by the examples of trees that are provided. However, we also believe that, by itself, this distance measure does not convey all nec-essary information for building phylogenies. Instead, it should be regarded as potencially useful for working in cooperation and complementing other measures.

Materials and methods

DNA sequences

In this study, we used the complete DNA sequences of 29 species: 27 were obtained from the National Center for Biotechnology Information (NCBI) (ftp://ftp.ncbi.nih.gov/genomes/); Populus trichocarpa (California poplar) obtained from the Joint Genome Institute (http://genome.jgi-psf.

org/) and Xenopus tropicalis (Western clawed frog) from Xenbase (http: //www.xenbase.org/). The species used in this work are listed in Table 1.

Distance to the nearest dissimilar

Consider the alphabet A = {A, C, G, T} and let s = (s k ) k∈{1,...,N } be a symbolic sequence defined in A. Consider a numerical sequence, w x , that represents the distance to the nearest dissimilar of symbol

x ∈ A. As an example, the four ND distance sequences for the short DNA fragment CAAACCGTTTAAGTAACAGGGATATTGGCCC are

w A = (3, 2, 2, 1, 1, 1), w C = (1, 2, 1, 3), w G = (1, 1, 3, 2), w T = (3, 1, 1, 2).
The global sequence of ND distances for this example is w = (1, 3, 2, 1, 3, 2, 1, 1, 2, 1, 1, 3, 1, 1, 1, 2, 2, 3). Chlamydia trachomatis str.D/UW-3/CX (bacterium) NC000117

Mycoplasma genitalium str.G37 (bacterium) NC000908

Streptococcus mutans str.UA159 (bacterium) NC004350

Streptococcus pneumoniae str.ATCC 700669 (bacterium) NC011900

Aeropyrum pernix str.K1 (archaeota) NC000854

Note that the ND distance of each nucleotide corresponds to the repeat length of that nucleotide.

w i = N, ( 1
)
where L is the length of w. Let n i be the number of occurrences of ND distance i, then

K i=1 n i i = N, ( 2
)
where K is the largest ND distance present in the data sequence. The mean distance is

L i=1 w i L = N L .
(3)

Relationship between ND and IN distances

In general, the ND distance distribution complements the information that is accumulated in the first IN distance. We recall that the IN distance is the distance to the first occurrence of the same nucleotide. Let n i be the absolute frequency of the i th IN distance,

n 1 = K i=2 n i (i -1) + δ = N -L + δ (4)
and

K i=2 n i = K i=1 n i -δ = L -δ, ( 5
)
where

δ = ⎧ ⎨ ⎩ 0, s 1 = s N 1, s 1 = s N
and K is the largest IN distance present in the data sequence. The last equation can be described by the following sentence:

the number of IN distances greater than one is equal to the total number of ND distances. As an illustration, the computed values for the previous DNA fragment example are: N = 31, n 1 = 14, L = 18, δ = 1.

Comparison with an independent random process

In order to calculate some statistical properties of various genomes, we will study the characteristics of the ND distance distribution.

Consider p A , p C , p G and p T the occurrence probabilities of nucleotides A, C, G and T, respectively. If the nucleotide sequences were generated by an independent and identically distributed (i.i.d.) random process, then each of the distances, W x , would follow a geometric distribution of parameter 1 -p x .

In fact, the probability distribution of the distance to the nearest dissimilar for symbol x is

f x (k) = P (W x = k) = P (W = k|x) = (1 -p x )(p x ) k-1 , k = 1, 2, ... (6)
Figure 1 shows the measured and the reference distributions of the ND distance sequences for the Homo sapiens complete genome. Although the ND distance distribution from DNA shows an exponential behavior, it differs from the reference distribution. This is expected, since the reference distribution was established under the assumption of an i.i.d. random process (with constant nucleotide relative frequencies estimated from the DNA sequence).

We performed the chi-square goodness of fit test with the result that the distributions are significantly different (all p values < 10 -4 ). In order to measure the differences between the observed and the reference distributions we used the Kullback-Leibler divergence.

Assuming that the DNA sequence was generated by an independent random process with constant parameters, the corresponding global ND distance sequence distribution is given by

f (k) = P (W = k) = x∈A P (W = k|x)P (x) = x∈A (1 -p x )(p x ) k . (7)

Numerical procedure

The histograms of the ND distance sequences were computed for each nucleotide and also for the global sequence. For large genomes and for convenience, the sequences were divided into blocks of 500 000 symbols. This procedure does not influence the total nucleotide counts. For eukaryote genomes, the chromosomes were processed separately and the resulting distance histograms were stored separately. All the symbols in the sequence that did not correspond to one of the four nucleotides were removed from the sequences before further processing.

We setup to investigate how similar (or different) are the observed and the reference distributions of:

• The four nucleotides of Homo sapiens;

• The chromosomes of Homo sapiens;

• Various species.

In order to facilitate the visual comparison of the various distance distributions with the theoretical one and to subtract the random background, we used the relative error, as given by

r(k) = f o (k) -f (k) f o (k) , ( 8
)
where f o (k) is the observed relative frequency of the distance k, and f (k) is the relative frequency of the reference distribution.

For the prokaryote species the values of the relative error of the ND distance were truncated to values between -1 and 1. We also used the IN distance relative error used in [START_REF] Afreixo | Genome analysis with inter-nucleotide distances[END_REF] and we concatenated the first 100 IN distances and the first 20 ND distance relative errors. Only the first 20 ND distances were used, because for larger distances the distributions become sparse. We have found that the limitation to the first 20 distances, which was carried out in all numerical experiments described in this paper, provides an adequate compromise between the information content and the vector length. Note that 792 is the largest ND distance for all the studied species and that the maximum proportion of the ND distances above 20 is 0.13%.

Results

Distances analysis

We compared the observed ND distance distributions of all Homo sapiens chromosomes and we obtained very small Kullback-Leibler divergence (< 0.0008). We have also compared, using the Kullback-Leibler divergence, the ND distance distribution of the four nucleotides of the Homo sapiens complete genome. The results of the comparative tests are shown in Table 2,

showing that the ND distance distribution of nucleotide A is closer to that of nucleotide T than to the other two nucleotides, and the ND distance distribution of C is closer to that of nucleotide G than to the other two nucleotides. Notice that the DNA complementary sequence was not used in A C G T A 0.00 0.04 0.04 0.00 C 0.03 0.00 0.00 0.03 G 0.03 0.00 0.00 0.03 T 0.00 0.04 0.04 0.00 the computation of the distributions. These identical distance distributions for the nucleotides A/T and C/G are present in all the human chromosomes and also in the genome of all the other species used in this work. This may be explained by the Chargaff's second parity rule and the extension of this rule (see for example [START_REF] Qi | Compositional symmetries in complete genomes[END_REF]; [START_REF] Albrecht-Buehler | Asymptotically increasing compliance of genomes with Chargaff's second parity rules through inversions and inverted transpositions[END_REF][START_REF] Albrecht-Buehler | Inversions and inverted transpositions as the basis for an almost universal "format" of genome sequences[END_REF]).

We used the relative error, as defined in ( 8), to compare the ND distance distributions, both for nucleotides and global sequences, with the reference distributions. This corresponds to removing the contribution of the random background to the ND distance distribution [START_REF] Qi | Whole proteome prokaryote phylogeny without sequence alignment: A K-string composition approach[END_REF]. For the global ND distance (Figure 3) of the human genome, the first two distances have a lower frequency than the one corresponding to ran-dom sequences, whereas the other distances have higher frequencies. The relative frequencies of distances above two are higher than in the reference distribution. The repetition of three or more nucleotides is more frequent in the human genome than in a random sequence. This pervasive existence of repeats is a well known characteristic of the human genome.

Analysis of multiple organisms

The ND distance relative error vectors of each complete genome may be used as a genomic signature that identifies each species, thus allowing the comparison of species (e.g. by building phylogenetic trees). We used the UPGMA programs in the PHYLIP package (http://evolution.genetics.

washington.edu/phylip.html) to build the phylogenetic trees (the similarity matrix was computed using the Euclidean distance).

The comparison of the various phylogenetic trees was carried out with TOPD/FMTS software [START_REF] Puigbo | TOPD/FMTS: a new software to compare phylogenetic trees[END_REF] and using the split distance (a low split distance value is synonymous of a high number of common branches between the two trees).

Hierarchical clustering was applied to a matrix composed by the first 20

ND distances for all the species used in this study. Figure 4 shows the phylogenetic tree for all the species in this study. The phylogenetic tree (obtained with complete linkage) displays a first branching between prokaryotes and eukaryotes, showing most of the mammals together. Moreover, all vertebrates are in the same cluster, the only two non-vertebrates in that cluster are: A. mellifera and V. vinifera. Fungi are also grouped together. The bacteria are displayed close together and the archaeota further apart.

With the ND distance relative errors we obtained an interesting tree that shows some of the evolutive features. However, we could point several unexpect clusters which may be due to the use of small vectors (20 elements)

to characterize the species. In parallel, we have developed methodologies based on the IN distances that can be complemented with information from the ND distances. These two methodologies are complementary: both describe distances between nucleotides, but in two different ways (see 2.2.1).

Figure 5 shows the phylogenetic tree constructed with a species vector that corresponds to the concatenation of the IN (removing the first IN distance)

and ND relative errors. We compare the results obtained by the IN-ND concatenation method with the IN, ND and random methods in Table 3.

The concatenation method obtains a tree topology similar to the IN method, but the changes introduced produced a better phylogenetic tree, including a higher fungi and archaeota differentiation. The differences between Figure 7 shows the normalized split distance between alignment algo- The normalized split distance is the number of splits in one tree, but not present in the other, divided by the total number of splits in the tree. The IN-ND concatenation method shows a small split distance value (similar to those obtained by [START_REF] Sims | Whole-genome phylogeny of mammals: evolutionary information in genic and nongenic regions[END_REF]) which reveals that the IN-ND concatenation contains relevant information about the phylogenetic evolution.

Conclusion

The ND distance mapping contains information about nucleotide repetition structure in the DNA sequence and characterizes the lengths of the single nucleotide repeats. An interesting feature of the ND distance approach is the strong similarity found for the A/T and C/G nucleotides. This may be explained by the existence of inverted repeats and by the second Chargaff parity rule and its extensions [START_REF] Qi | Compositional symmetries in complete genomes[END_REF][START_REF] Albrecht-Buehler | Asymptotically increasing compliance of genomes with Chargaff's second parity rules through inversions and inverted transpositions[END_REF][START_REF] Albrecht-Buehler | Inversions and inverted transpositions as the basis for an almost universal "format" of genome sequences[END_REF].

Since the ND distance vectors are small (around 20 elements) and the IN distance characterizes the distance between groups of single nucleotide repeats, we concatenated the IN and ND distances in order to obtain a vector that better differentiates species.

The results obtained in this work suggest that, for the addressed species, there is a genetic signature, a vector with the concatenation of the relative error of the IN and ND distances, that is a distinguishing characteristic of each species.

Acknowledgments

This work was supported in part by the FCT (Fundação para a Ciência e Tecnologia). Sara P. Garcia acknowledges funding from the European Social Fund and the Portuguese Ministry of Science, Technology and Higher Education.

Algorithm 1 .

 1 Computation of w for sequence s p

Figure 2

 2 Figure 2 shows the relative error for the ND distance for each nucleotide of the Homo sapiens genome and Figure 3 the relative error for the global ND distance sequence. A relative error close to zero means that the observed frequency is similar to that of the reference distribution. Values close to one imply observed distances much more frequent than in the reference distribution.

  Figures 4 and 5 may arise from the use of larger vectors in Figure 5 (119 elements), thus conveying more information than the ND distance vectors (Figure 4). Moreover, as already mentioned, the ND distance complements the information accumulated in the first IN distance. In order to compare alignment and alignment-free algorithms to construct phylogenetic trees Sims et al. (2009) used 10 mammals. Figure 6 shows the phylogenetic tree constructed for the same set of mammals as used by Sims et al. (2009), using the IN-ND concatenation method. The topology of the phylogenetic tree obtained using the IN-ND concatenation method is similar to the phylogenetic trees presented by Sims et al. (2009) for alignment based algorithms (Type I, Type II, Prasad et al. (2008)).

Figure 1 :Figure 2 :

 12 Figure 1: Distribution of the four nucleotide ND distance sequences for the Homo sapiens genome. The histogram is from the observed distances and the solid line shows the reference distribution with parameters estimated from the data.

Figure 3 :

 3 Figure 3: Relative error for the global ND distance distribution in the complete genome of Homo sapiens (first 20 distances).

Figure 4 :

 4 Figure 4: Phylogenetic tree with the species used in this study, using the 20 ND distances.

Figure 5 :

 5 Figure 5: Phylogenetic tree with the species used in this study, using the IN-ND concatenation method.

Figure 6 :

 6 Figure 6: Phylogenetic tree with the 10 mammals used in this study, using the IN-ND concatenation method.

Figure 7 :

 7 Figure 7: Normalized split distances between phylogenetic trees constructed with multiple sequence alignment and free-alignment methods.

Table 1 :

 1 List of DNA builds used for each species.

	Species

Table 2 :

 2 Kullback-Leibler divergence values between the ND distance distribution of the four nucleotides in the Homo sapiens genome.

Table 3 :

 3 Normalized split distances of the 29 species.

	ND	IN	Random
	IN-ND 0.7692 0.1154 0.9888
	rithms and alignment-free algorithms (Sims's methods and our methods).


Sara Van Rompaey

Jacques Kimfuta

Pierre Kimbondo

Cecilia Monn

Anne Buvé

Operational assessment of access to ART in rural Africa: the example of Kisantu in Democratic Republic of the Congo

published or not. The documents may come

HIV prevalence in DRC has recently been estimated at 1.3 %.( 1) The Demographic and Health Survey estimates the prevalence in people living in urban and rural areas at 1.9 and 0.7 % respectively.

Despite the availability of large funds and considerable efforts to improve access to ART (Antiretroviral Therapy) [START_REF]Rapport national de situation à l'intention de l'UNGASS[END_REF] , coverage of treatment with ART in DRC is low. The WHO '3 by 5' target for DRC was people who were receiving ART on the 30 th June 2007 4 . With coverage of less than 10%, DRC is classified amongst the worst countries in the world in terms of scaling up. [START_REF]Report on the global AIDS Epidemic[END_REF] According to national data, only 4.1 % of all adults have been tested for HIV in a year's time (3), which suggests that lack of HIV testing is an important bottleneck. 70% of HIV positive patients who started ART are still in therapy 12 months after the initiation. A major obstacle for appropriate ART Delivery Programs is patient loss to follow up. High rates (35%) of loss to follow-up > 6 months since the last clinic visit have been reported in DRC. Cumulative incidence of death among lost patients is high. [START_REF] Atibu Losoma | Losses to follow-up in 3 Central African country non-PEPFAR ART delivery programs[END_REF] No data are available on the total number of the detected HIV positive people who registered at an HIV care programme, Transmission) programme is implemented, are advised to be tested for HIV, using an opt-out strategy.

neither
Kisantu has 4 TB centres for diagnosis and treatment. Three of them are rural and the fourth is located in the hospital. HIV testing is only available for TB patients treated in the hospital site, according to an opt-out strategy.

CD4 counts are only freely available for TB/HIV co-infected patients. For the other patients, eligibility is based on clinical staging and total lymphocyte count, according to the national guidelines. All patients, whether eligible for ART or not, are asked to visit the HIV clinic every month.

Framework for estimation of patients' flow

The flow model used in this study is based upon an operational model for the analysis of TB control programmes, developed by MA Piot (1967), who at that time was attached to WHO. [START_REF] Piot | A simulation model for case finding and treatment in tuberculosis control program[END_REF] In this study our simplified model has 4 steps (Figure 1). For the first part of the study, census data of the population of Kisantu health zone, obtained at the database of the Ministry of Health, are used. In the Demographic and Health Survey of 2008 (1), about 50 % of the population of RDC is estimated to be older than 15 years. We used the regional prevalence of 0.7%, observed in Western DRC (1).

Data collection

The number and residence (urban or rural or outside of Kisantu health zone) of people tested at each HIV testing site, and the proportion of HIV positive tests results, were collected from the monthly reports of the health zone, the anonymous VCT forms of the hospital and the TB patients' monitoring register.

For all patients who accessed the HIV care programme, the residence of the patient and the initial testing site were extracted from the HIV care programme's registers. The patients' personal files were checked for eligibility and anonymously compiled on another form.

ART eligibility status was checked using the national criteria for initiation of antiretroviral treatment [START_REF]Guide national de traitement de l'infection à VIH par les antirétroviraux[END_REF] .

The number and residence of patients starting ART were extracted in an anonymous way from the ART register of the HIV care programme. According to data from the WHO [START_REF]Global tuberculosis control -epidemiology, strategy, financing[END_REF] tuberculosis report 2009, the national incidence rate of tuberculosis is estimated at 392/100 000 pop/year and the HIV prevalence in incident TB cases at 5.9%.

The estimation of the number of pregnant women in Kisantu is based on data published in the Demographic Health Survey. In Bas-Congo province, the prevalence of pregnancy is 9.6 % among women between 15 and 49 years. For a population of 144 395 inhabitants, 3032 women are estimated to be pregnant at any one time.

According to official reports from Kisantu health zone, the HIV prevalence of pregnant women in the PMTCT programme is 0.6%.

Ethical approval

The study was approved by the ethical committee of the School of Public Health of the University of Kinshasa.

Results

Proportions of PLWHA in the operational flow

During the study period an estimated 505 adults in Kisantu health zone were living with HIV, of whom 266 (53 %) were identified in the HIV testing sites and 239 HIV infected adults remained unaware of their condition. 62 people who were identified with HIV during the study period were living outside of Kisantu health zone. Of the 266 PLWHA of Kisantu health zone that were identified, 163 (61 %) accessed the hospital's HIV care programme during the study period. 10 PLWHA who accessed the HIV care programme were living outside Kisantu health zone. 126 of those living in Kisantu health zone who accessed the HIV care programme were identified as eligible and four as non eligible for ART. For 33 patients who were not initiated on ART, eligibility status remained unknown, as their personal files could not be found in the hospital. The exact number of eligible patients is thus between 126 and 159 patients.

106 eligible patients living in Kisantu health zone initiated ART. Between 20 and 53 eligible patients got lost at this step. In the urban area of Kisantu, 41 % of the estimated PLWHA accessed the HIV care programme and 65% of the estimated 145 patients in need initiated ART. In the rural area, 11% of all PLWHA accessed the HIV care programme and 21% of the estimated 56 patients in need initiated ART.

Proportions of patients in different HIV testing sites 6,451 adults have been tested for HIV in the health zone during the study period. 328 of them tested HIV positive, resulting in an average prevalence of 5% for all testing settings together.

Table 2: comparison of outcomes of different HIV testing sites

The estimated number of TB patients in the health zone is 566 per year, so 1,557 for the whole study period. 92 patients amongst them are estimated to be infected with HIV, of whom the TB programme detected 75%.

The estimated yearly number of pregnant women in the health zone is 3,032, which means 8,338

pregnant women for the whole study period. 50 pregnant women were estimated to be infected with HIV, meaning that the PMTCT programme detected 48% of the estimated number of HIV positive pregnant women in the health zone.

The TB and PMTCT programme together could theoretically detect 142 patients, which is 28% of the estimated 505 PLWHA living in the health zone, as illustrated in table 3.

Table 3: potential and actual coverage of the TB programme and PMTCT programme

Discussion

Limitations of the study

There are several aspects of the study design that call for some caution in the interpretation of the results. Firstly, the data used in this study highly depend on the estimation of the prevalence of HIV, TB, and fertility rates of the general population. Secondly, this is a small-scale study with rather small proportions of patients, especially at the later steps of the model. Extrapolation of these data might not Although the study evaluates how many patients reach the steps of the operational flow within the study period, it does not reveal how much time patients take to proceed to the next step. E.g. an HIV positive person, who is ignorant of his status today, may want to go for testing in a few years' time, when he will become aware of his HIV-related symptoms. The exact outcomes of the drop-offs remain unknown and therefore it cannot be determined in which group of drop-offs the highest mortality occurs, neither which proportion in each group of drop-offs will proceed eventually to the next step. In fact, any definition of loss to follow-up at any step of the flow model can be seen as arbitrary as a patient who is late can never be considered as definitively lost unless he is reported to be dead.

However, even if the proportion of dead patients among patients lost to follow-up is unknown, loss to programme can undoubtedly be seen as a program failure indicator.

Furthermore, CD4 counts are not systematically quantified in each patient, which does not allow a precise evaluation of the grade of immunodeficiency and therefore severity of disease in registered patients.

This study provides only quantitative data, but to gain more insight in the determinants behind the awareness and health-seeking behaviour of the population, identified as two important bottlenecks, qualitative studies are needed. Aspects that have not been covered in this study are the quality of counselling and HIV care, children's access to ART, psychosocial follow-up, adherence to ART and prevention. Other studies are needed to cover these aspects.

Proportions of PLWHA in the operational flow

The estimated ART coverage is much higher in Kisantu (53%) than nationally (less than 10%) because in the majority of health zones of DRC the HIV care programme is not implemented, due to insufficient funding.

Poor coverage of HIV testing has been explained in other resource-limited contexts by poor healthseeking behaviour, stigma in society and operational challenges. Apart from two health centres with a PMTCT programme, all testing sites are located in the urban area. Transportation problems are probably the main obstacle for people living in rural areas. In a successful program of scaling up VCT in Kenya [START_REF] Marum | Scale-up of Voluntary HIV counseling and Testing in Kenya[END_REF] , similar findings have been documented: 'The national target number of testing sites has been exceeded, although the target number of sites for each district has not been achieved in the districts in remote or hard-to-reach areas, and a program to increase mobile VCT tries to compensate for this poor access.' In DRC, decentralisation of VCT to the health centres and health posts might be a good solution, but many personnel will have to be trained. Furthermore, it will be difficult to overcome the inequity in access to the HIV care programme, if over time its provision will still remain in one central site. According to WHO, many countries suffer from urban concentration of health professionals and rural deficits. [START_REF]World Health Organisation (WHO) Health worker shortages and the response to AIDS[END_REF] Strategies to decentralise HIV care should be developed, as in Lusikisiki, in rural South-Africa, where a greater proximity and acceptability of services at the clinic level led to faster enrolment of people receiving treatment. [START_REF] Bedelu | Implementing Antiretroviral Therapy in Rural Communities: The Lusikisiki Model of Decentralised HIV/AIDS Care[END_REF] The second biggest bottleneck, being access to the HIV care programme for those who have been identified with HIV, could be regarded as more crucial because the HIV care programme is not capable of treating all patients that are detected. The explanation is probably multifactoral. It may be due to a poor referral system between the testing sites and the HIV care programme or related to the health seeking behaviour of people tested HIV positive. A high proportion of PLWHA who accessed the HIV care programme is eligible, which means that people are detected and/or registered when they may be aware of their illness. The fact that ART coverage in all eligible patients in the health zone is better than the PLWHA coverage of the HIV care programme, suggests that the HIV care programme selected the more severe 'eligible' cases.

Outcomes of different HIV testing services

The good flow of the TB/HIV co-infected patients to the HIV care programme and the high loss to follow up of HIV infected pregnant women, are probably explained by the patients' awareness of their health status. This study shows that tuberculosis control programmes have a great potential of identifying persons infected by HIV in settings with low HIV prevalence: with only a low percentage of TB patients who have been tested for HIV, a high proportion of HIV patients of the health zone are picked up by the programme, because health care worker-initiated settings of hospitalised patients and persons suspected of having tuberculosis are ideal settings in which to identify large numbers of persons with advanced HIV infection (12). The high uptake of HIV testing in the maternity departments and the TB programme is most likely linked to their opt-out strategy. Looking at the proportions that accessed the HIV care programme, the identified bottleneck also seems to be linked to operational aspects of HIV the testing site. The community-based VCT site (with 75% access of HIV positive patients to the HIV care programme) routinely performed active follow-up of those tested positive.

With the observed HIV prevalence of 0.6% in pregnant women, the PMTCT programme could theoretically detect 10% of all PLWHA, by testing 11.6% of the total adult population. However, the prevalence we observed might be under-estimated as in Bas-Congo province, 2% of women in PMTCT programmes were tested HIV positive 15 . On the other hand, according to a survey of UNAIDS in sub-Saharan Africa 16 , the HIV prevalence of women attending ante-natal clinics is 1.25 times higher than the prevalence obtained by a demographic health survey, which would for Bas-Congo would mean 0.87% of pregnant women. The opt-out strategy in the PMTCT programme has only a small impact on the health status of the HIV positive mothers in Kisantu, because a limited proportion of them obtain HIV care, as has been shown

in other studies as well 1718 . Improving the referral system between PMTCT programs and the HIV care programme is a priority. In the TB clinic, patients had regular appointments to collect the TB drug, and a detailed register allowed tracking of each co-infected patient. DOTS has been used now for many years to provide successful anti-tuberculosis treatment to millions of patients in poor countries of the world, and the ART programme may benefit from many of the established concepts of a TB programme. 19 Based on the better performance of TB programmes in detection, referral and care of people found to have HIV infection, other programmes like those of STI control and reproductive health care would benefit from a more standardized approach with an opt-out strategy of HIV testing and a more rigorous referral and treatment protocol.

We also suppose that TB patients who suspect they are co-infected with HIV may be more likely to seek care at the TB clinic of the referral hospital, the only TB treatment centre that performs HIV testing. Alternatively, the prevalence of HIV in TB patients may be substantially higher in Kisantu (15%) than the national numbers presented by WHO (5.9%), which would increase the actual yield of the TB programme.

In conclusion, the model we used allowed us to identify two important bottlenecks of access to ART, and helps to decide on which approach to adopt to improve access. The probability that a patient does proceed from one step to the next is a measure of the performance of different disease control activities. Poor coverage of HIV testing has been detected in other studies, but more research is required to discover the exact underlying causes for the high loss to follow-up of people with a positive HIV test result. Further investigation could identify weaknesses in the referral system of the programme, patients' possible denial of the test result, adherence to an alternative care circuit or death. Drop-offs at different levels have not only been observed in ART programs, but also in studies of control of sexually transmitted diseases 20 and tuberculosis 21 .

Given the low rate of loss to follow-up at all steps of patients with TB/HIV co-infection, who benefit from a rigorous approach, we think that the way forward for other disease control programmes is to integrate HIV care in a standardized way. Improving the referral system between PMTCT programs and the HIV care programme is a priority. This study takes into account all activities related to the HIV care program, and gives therefore a realistic overview of the strengths and weaknesses at each level.

Loss to follow-up at any step of the programme is a crucial indicator of failure of programme performance in tracking the outcomes of care. Eligible patients PLWHA registered

Step 1

Step 2

Step 3

Step

  Operational assessment of access to ART in rural Africa: the example of Kisantu in Democratic Republic of the Congo Introduction Since its independence in 1960, the Democratic Republic of the Congo (DRC) has faced economic decline 1 , resulting in a low per capita GNP, limited reach of government services, and break down of communication systems and infrastructure. In the 2010 index of failed states 2 , DRC is ranked the fifth worst country in the world. DRC is facing enormous challenges to provide health care, including HIV care. Gaps left by the government are filled by numerous non-governmental and faith-based organizations.

  ART. The Global Fund's Performance Monitoring Report mentions only 13064

  about the proportion of eligible patients amongst patients registered and the proportion of eligible patients who initiated ART, in DRC.The aim of this research is to identify the bottlenecks of access to ART in a health zone in DRC, using an operational model. The study compares the proportion actually on ART with the estimated number in need of ART. It identifies the problems that arise at different steps of an operational flow model,[START_REF] Dujardin | Editorial: Tuberculosis control: did the programme fail or did we fail the programme?[END_REF] by evaluating the proportion of HIV positive people who know their HIV status, the proportion of those who access the HIV care programme, the proportion of eligible patients at clinic level and the proportion initiating ART. The study compares access for patients living in the urban and rural areas of the health zone. It compares HIV prevalence, and access to the HIV care programme in patients tested in different testing settings. It evaluates the yield of the different HIV testing sites and estimates their potential to detect an important number of people living with HIV.MethodsSettingKisantu is a semi-rural health zone in Bas-Congo province with a surface of 240 square kilometres and an estimated total population of 144,395 inhabitants, 73,205 of whom live in the urban area of Kisantu town and 71,190 in rural villages. The main economic activity is subsistence farming (70 % of the active population) while 20% of the population make a living with small-scale commercial and other informal activities, and 10% is employed by the government.Based on data from the Demographic Health Survey, HIV prevalence in Kisantu is roughly estimated at 1% for the urban population and 0.4% for the rural population. The HIV care programme is integrated and centralised in the mission hospital Saint Luc, located in Kisantu town, and managed by the Ministry of Health. No health care providers outside this programme are providing ART.The programme receives rapid antibody tests, antiretroviral medicines and drugs for opportunistic infections treatment funded by the Global Fund to Fight AIDS, Tuberculosis (TB) and Malaria.

3 HIV

 3 testing is performed in the hospital, in 2 rural and 3 urban maternity wards, in the TB diagnostic and treatment centre located in the hospital, and in one urban community-based VCT (Voluntary testing and Counselling) centre. The HIV testing site in the hospital receives referrals by clinicians as well as clients who wish to know their HIV status on a voluntary basis. All pregnant women presenting at the ante-natal clinics in the five maternities where a PMTCT (Prevention of Mother-To-Child

Figure 1 :

 1 Figure 1: simplified model for operational flow of PLWHA

4

  Proportions of patients in different HIV testing sitesIn order to estimate the yield of different types of testing sites like the TB programme and the PMTCT programme, we used the following formula: Potential number of PLWHA to be detected by TB programme = estimated number of TB patients in the health zone x estimated HIV prevalence in TB patients Coverage of HIV testing in TB patients = TB patients tested for HIV Estimated N TB patients Coverage of PLWHA detected at TB testing site = number of TB/HIV co-infected patients tested Expected number of PLWHA detectable by TB programme Potential number of PLWHA to be detected by PMTCT programme = estimated number of pregnant women x estimated HIV prevalence in pregnant women in DRC Coverage of HIV testing of PMTCT program = pregnant women tested for HIV Estimated number of pregnant women Coverage of PLWHA detected in PMTCT programme = Number of HIV positive pregnant women tested Expected number of PLWHA detectable by PMTCT programme

5 All

 5 PLWHA with residence outside of Kisantu health zone were excluded from the analysis of the patients' flow, but were included in the evaluation of the performance of different testing sites and the yield of TB and PMTCT programmes.

  of a large-scale HIV programme. A large-scale study containing data of different health zones, or a country national level, would be interesting in this respect.

11 20Figure 1 : 3 N

 1113 Figure 1: simplified model for operational flow of PLWHA, page 3

Table 1 :

 1 proportions of adult patients according the different steps in the flow programOverall 32 % (53 % x 61 %) of the estimated number of adult PLWHA in the health zone accessed the HIV care programme. According to the outcomes of the analysis with the Spectrum software package, 201 patients were estimated to be in need of ART in Kisantu during the study period. With 106 patients who were initiated on ART, ART coverage of 53 % was reached.

	F o
	r
	P
	e e r
	R e v i e w
	O n
	l y
	6

Table 1 :

 1 4 proportions of adult patients according the different steps in the flow program, page 5

	Proportion:
	N starting ART
	N Eligible

Table 2 :

 2 comparison of outcomes of different HIV testing sites, page 6

		Hospital testing site (n + and % of n PLWHA in previous step)	Community VCT (n + and % of n PLWHA in previous step)	PMTCT programme (n + and % of n PLWHA in previous step)	TB programme (n + and % of n PLWHA in previous step)	Total (n + and % of n PLWHA in previous step)
	N tested	1125	699	4152	475	6451
	N HIV +	195 (17%)	40 (6 %)	24 (0.6%)	69 (15%)	328 (5%)
	Number
	accessing HIV	71 (36%)	30 (75 %)	3 (13%)	69 (100%)	173 (53%)
	care programme

Proportion of all 173 patients who accessed the HIV care programme

	41%	17%	1.7 %	40%	N/A

Table 3 :

 3 potential and actual coverage of the TB programme and PMTCT programme, page 6

		TB programme	PMTCT programme
		Estimation of potential yield	Actual coverage (n and % of potential yield)	Estimation of potential yield	Actual coverage (n and % of potential yield)
	Total number of people
	reached by the	1557	742 (48%)	8338	6721 (80%)
	programme
	Total number of people tested for HIV	N/A	475	N/A	4175

http://mc.manuscriptcentral.com/ac-phm-vcy Health Sciences

http://mc.manuscriptcentral.com/ac-phm-vcy

Libamba E,et al. (2005) Scaling up antiretroviral therapy in Africa: learning from tuberculosis control programmes--the case of Malawi. Int J Tuberc Lung Dis.9(10):1062-71.