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Currently, there is limited information on the circulating HIV-1 strains, the distribution of these strains and antiretroviral ART resistant viruses in different regions of the country, and the HIV-1 strains harbored by the high-risk groups like female sex workers FSW reported to be the source of recombinant and ART resistant viruses. Regional segregation of HIV-1 clades was detected using phylogenetics. The ificance for differences in HIV-1 subtype and drug resistance mutations were evaluated using Chi-square tests.


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The child mortality rate is a good indicator of development. Recent conflicts in the eastern part of the country and bad governance have compounded the problem. This study aimed to examine province-level geographic variation in under-five mortality U5Ming for individual- and household-level risk factors including environmental factors such as conflict. Our analysis used the nationally representative cross-sectional household sample of 8, children under five in the DRC Demographic and Health Survey.

In the survey year, 1, deaths among this group were observed. Information on U5M was aggregated to the 11 provinces, and a Bayesian geo-additive discrete-time survival mixed model was used to map the geographic distribution of under-five mortality rates U5MRs at the province level, ing for observable and unobservable risk factors.

The overall U5MR was per 1, live births. This study reveals clear geographic patterns in rates of U5M in the DRC and shows the potential role of individual child, household and environmental factors, which are unexplained by the ongoing conflict. The displacement of mothers to safer areas may explain the lower U5MR observed at the epicentre of the conflict in North Kivu, compared with rates in conflict-free areas.

Peer Review reports. The child mortality rate is considered the best proxy indicator of general population health and the level of socioeconomic development [ 1 ].

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The child mortality rate is also a useful marker of overall development and a Millennium Development Goal MDG indicator [ 2 ]. A high rate of mortality among children reflects precarious conditions such as poor nutrition, low access to drinking water and inadequate health services [ 1 ]. In Sub-Saharan Africa SSAseveral conditions influence infant mortality, including hygienic, socioeconomic, cultural, environmental and geographic factors [ 3 ].

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However, geographical associations with mortality have been neglected. Thus, it is a worthwhile endeavour to investigate the trends, geographic patterns and associations of child mortality rates [ 4 ]. Of SSA countries, the DRC has the third largest population and the second largest land area, distributed across 11 provinces see Figure 1. The DRC has high rates of infectious disease and child mortality [ 5 — 7 ]. A second factor involves the uneven distribution of access to health care, health services infrastructure and development. A third factor is that the recent conflict that has exacerbated this situation [ 13 — 15 ].

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Map of the Democratic Republic of Congo showing crude under-five mortality rate by province. Overall mortality rate was deaths per live births weighted data. The often disastrous impact of complex emergencies in the DRC on public health has been widely documented by international entities and nongovernmental organisations [ 12 — 16 ].

The war has devastated and destabilised the country, claiming the lives of about six million civilians [ 13 — 16 ]. Compared with other conflicts over the past centuries, the consequences have been similar in nature but on a much greater scale [ 8 ]. Despite the presence of more than 17, United Nations UN peacekeepers, a major UN deployment, the situation in the DRC continues to be a matter of great concern for the international community [ 14 — 16 ].

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The combined effects of this war and the preceding decades of poor governance and mismanagement have contributed to the impoverishment of the DRC [ 8 — 12 ]. In the health sector, the low level of social indicators shows the catastrophic impact that the conflict has had on living conditions, particularly for women and children.

Life expectancy at birth, which was estimated at In many parts of the country, people live in dismal conditions, and what remains of foreign armies in the DRC continue to cause havoc and adversely affect public health services [ 13 ].

Various militia groups operating in the eastern provinces continue to use rape as an instrument of war and destroy an already inadequate public health service [ 12 — 15 ].

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Despite the vast mineral wealth of the country, health, nutrition and population outcomes in the DRC remain extremely poor. This makes it difficult for the country to achieve the MDGs. The infant mortality rate is above the overall average for Africa of per 1, and stands out as one of the most alarming in the region [ 17 — 202324 ].

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However, the available figures suggest that child mortality in the DRC remains among the highest in the world [ 117 — 202324 ]. To produce robust estimates, we adopted novel approaches to take into uncertainty in sampling variation given the existence of various measured and unmeasured factors such as conflicts. The findings of this study highlight geographic patterns that may provide insights for humanitarian intervention and policy formulation.

For the DRC-DHS, data were collected from a nationally representative sample of 9, households 3, in urban areas and 5, in rural areas. Complete interviews were conducted with 9, women aged 15—49 and 4, men aged 15—59 [ 5 ]. In addition to standard modules or sets of questions, we sought to establish background characteristics such as contraceptive knowledge and practice, marriage and AIDS knowledge, complete birth history, nutrition, immunisation and health information about each child under 5 years of age at the time of the survey.

Birth history data were collected for each of the women interviewed. For each birth, questions were asked about the date of birth, name, sex, survival status and age at death if deceased. This information allowed us to investigate mortality patterns and unearth the determinants of U5M during this period. This study uses the available information on 9, women and 8, live births occurring in the 5 years preceding the survey.

In general, the DHS data are of good quality, covering all regions including both urban and rural areas in the DRC [ 5 ]. However, the survey is cross-sectional. The DHS was carried out after the elections from February 2 to April 30,for Kinshasa and from Discrete sex Dem Rep of Congo 10 to August 31,for the remaining provinces.

At the time, some villages and municipalities in the eastern provinces of North Kivu, South Kivu and Orientale were still experiencing armed conflict [ 5 ]. Therefore, the of our study might be affected by data quality issues owing to undercoverage or bias because of nonresponse or temporary migration caused by conflict. Data were analysed with relevant variables to carry out survival analyses for the first 5 years of life U5M: 5q0. We examined spatial variation in U5M with a flexible Bayesian geo-additive discrete-time survival model. This models mortality events as person-specific Cox processes while controlling spatial dependence and possibly nonlinear effects of covariates within a simultaneous and coherent regression framework [ 26 — 28 ].

The analysis was carried out using version 2. The statistical methods used have been discussed elsewhere [ 427 — 34 ] and are also provided as an additional file see Additional file 1. In the 5-year period preceding the survey, there were 1, reported deaths. Overall, the U5MR defined as the probability of dying between birth and exactly 5 years of age, expressed per 1, live births was U5MRs were higher in rural areas compared with urban areas Table 1 also shows the distribution of U5MRs by geographic location, revealing dramatic geographic disparities in observed crude U5MRs.

The mortality rate is very high in the provinces of Maniema, Orientale and South Kivu, estimated at Kinshasa and North Kivu are among the provinces with lower observed U5MRs compared with the national average. Table 4 displays both marginal and posterior odds ratios of U5M risks across the selected study characteristics. Left: Estimated nonparametric effect of baseline time child survival. There is a pronounced effect of the baseline time on child survival during the first months of life Figure 2 leftbut the excess risk persists through the first month period.

The baseline effects peak at 24, 30 and 36 months.


Higher mortality rates are observed among mothers giving birth at older ages 38 years and above. With regard to U5M risk in the marginal regression analyses, a striking variation was noted in the U5M risks across provinces.

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The highest risks were observed in Maniema province [1. Figure 3 shows the for the covariate-adjusted spatial variation of U5M status captured in terms of the global effects across provinces left i. Provinces in the west and other provinces in the east, in contrast, were associated with a lower risk of U5M. These spatial patterns confirm the observed marginal model findings shown in Table 4. Left: Total residual spatial effects of child survival at province level in the DRC.

Posterior odds ratio is shown.

Child mortality in the democratic republic of congo: cross-sectional evidence of the effect of geographic location and prolonged conflict from a national household survey

This is illustrated as a colour scale, with white denoting provinces with strictly negative credible intervals lower mortality and black showing provinces with strictly positive credible intervals higher mortality. The total residual spatial effects point to a slight advantage in terms of child survival in North Kivu.

The survival advantage for children in Bas-Congo, Bandundu and Kinshasa is captured by the unstructured localised spatial effects not shown herebut this is statistically inificant and shows how these local spatial effects are influenced by neighbouring effects. The ificance of this study lies in the finding that the high levels and variations of U5M in the DRC cannot be explained by the ongoing conflict. The study suggests that U5M is increasingly influenced by factors including hygienic and environmental conditions as well as socioeconomic and cultural variables, which persist within various social contexts [ 3 ].

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Several risk factors beyond the well-typically considered variables were examined. The effect of geographic location was explored and quantified as a proxy for environmental factors such as conflict. The findings indicate that spatial effects mediate mortality rates in conflict-affected countries such as the DRC. The spatial patterns may also mirror factors such as high fertility, which is characterised by short birth intervals.

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Nationally, the U5M was estimated at per 1, live births. This figure could be even higher in reality, because of the absence of official vital registries and because displacement and conflicts often influence record-keeping [ 12 ]. The use of geo-additive modelling has been crucial to disentangle the role of various competing factors contributing to higher mortality in this context. At the time of the survey, some provinces were and still are affected by ongoing conflict Maniema, North and South Kivu and Katanga.

Although conflict undoubtedly confounds the observed mortality rates, this study shows that conflict is not the only factor contributing to the excess mortality risks. Possible explanatory factors are the lack of programmes to improve child health and survival and the lack of access to adequate health services. However, in past decades, national programmes of this type have been lacking in implementation, leading to the position of the DRC as the lowest country worldwide in development indicators rankings [ 2122 ].