High prevalence of hepatitis B and HIV among women survivors of sexual violence in South Kivu province, eastern Democratic Republic of Congo.

INTRODUCTION: Limited data are available on the prevalence rates of hepatitis B and acquired immunodeficiency syndrome (AIDS) among women survivors of sexual violence (WSSV) in South Kivu province, in the eastern part of the Democratic Republic of Congo (DRC), where armed conflicts persist. Here, we aimed to assess the prevalence of these two infections in this vulnerable local population. METHODS: A total of 1002 WSSV, aged from 18 to 70 years old were enrolled from May 2018 to May 2020 at three healthcare facilities (Panzi, Mulamba and Bulenga hospitals), which are called "The One-Stop Centre Care Model" for the management of sexual violence in South Kivu. Blood samples were collected and tested for hepatitis B virus (HBV) and human immunodeficiency virus (HIV) antigens and antibodies using enzyme-linked immunoassay (ELISA) methods. Subsequently, viral load quantification for HBV and HIV were performed using the GeneXpert. Univariate and multivariate logistic regression models were used to assess factors associated with HIV-positive and HBV-positive status. RESULTS: For HBV, overall prevalence was 8.9% (95% CI; 7.2-10.8%), 32.1% (95% CI; 29.3-35.0%), and 14.5% (95% CI; 12.3-16.8%) for HBsAg, anti-HBc and anti-HBs antibodies, respectively. Among the 89 HBsAg-positive patients, 17 (19.1%) were HBeAg-positive. The median age of individuals with a positive HBsAg test was higher than those with a negative test (median: 40 years (IQR 30-52) compared to 36 years (IQR 24-48)). Risk factors for HBV infection were age (≥35 years) (AOR = 1.83 [1.02-3.32]; p = 0.041), having no schooling (AOR = 4.14 [1.35-12.62]; p = 0.012) or only primary school-level (AOR = 4.88 [1.61-14.75]; p = 0.005), and multiple aggressors (AOR = 1.76 [1.09-2.84], p = 0.019). The prevalence of HIV was 4.3% [95% CI: 3.1-5.7%]. HIV/HBV co-infection occurred only in 5 individuals (0.5%). The HBV viral load was detectable (> 1 log10 UI/mL) in 61.8% of HBsAg-positive subjects and 64.8% HIV-positive subjects had a high viral load (≥ 3 log10 copies/mL). CONCLUSION: This study revealed a high prevalence of HBV and HIV infections among WSSV in South Kivu. The results generated highlight the urgent need for systematic screening of HBV and HIV by integrating fourth-generation ELISA tests in HIV and HBV control programs.

Whole-genome sequencing of SARS-CoV-2 reveals diverse mutations in circulating Alpha and Delta variants during the first, second, and third waves of COVID-19 in South Kivu, east of the Democratic Republic of the Congo.

OBJECTIVES: We used whole-genome sequencing of SARS-CoV-2 to identify variants circulating in the Democratic Republic of the Congo and obtain molecular information useful for diagnosis, improving treatment, and general pandemic control strategies. METHODS: A total of 74 SARS-CoV-2 isolates were sequenced using Oxford Nanopore platforms. Generated reads were processed to obtain consensus genome sequences. Sequences with more than 80% genome coverage were used for variant calling, phylogenetic analysis, and classification using Pangolin lineage annotation nomenclature. RESULTS: Phylogenetic analysis based on Pangolin classification clustered South Kivu sequences into seven lineages (A.23.1, B.1.1.6, B.1.214, B.1.617.2, B.1.351, C.16, and P.1). The Delta (B.1.617.2) variant was the most dominant and responsible for outbreaks during the third wave. Based on the Wuhan reference genome, 289 distinct mutations were detected, including 141 missenses, 123 synonymous, and 25 insertions/deletions when our isolates were mapped to the Wuhan reference strain. Most of these point mutations were located within the coding sequences of the SARS-CoV-2 genome that includes spike, ORF1ab, ORF3, and nucleocapsid protein genes. The most common mutation was D614G (1841A>G) observed in 61 sequences, followed by L4715L (14143 C>T) found in 60 sequences. CONCLUSION: Our findings highlight multiple introductions of SARS-CoV-2 into South Kivu through different sources and subsequent circulation of variants in the province. These results emphasize the importance of timely monitoring of genetic variation and its effect on disease severity. This work set a foundation for the use of genomic surveillance as a tool for future global pandemic management and control.

Molecular Evidence of Coinfection with Acute Respiratory Viruses and High Prevalence of SARS-CoV-2 among Patients Presenting Flu-Like Illness in Bukavu City, Democratic Republic of Congo.

The coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with clinical manifestation cases that are almost similar to those of common respiratory viral infections. This study determined the prevalence of SARS-CoV-2 and other acute respiratory viruses among patients with flu-like symptoms in Bukavu city, Democratic Republic of Congo. We screened 1352 individuals with flu-like illnesses seeking treatment in 10 health facilities. Nasopharyngeal swab specimens were collected to detect SARS-CoV-2 using real-time reverse transcription-polymerase chain reaction (RT-PCR), and 10 common respiratory viruses were detected by multiplex reverse transcription-polymerase chain reaction assay. Overall, 13.9% (188/1352) of patients were confirmed positive for SARS-CoV-2. Influenza A 5.6% (56/1352) and Influenza B 0.9% (12/1352) were the most common respiratory viruses detected. Overall, more than two cases of the other acute respiratory viruses were detected. Frequently observed symptoms associated with SARS-CoV-2 positivity were shivering (47.8%; OR = 1.8; CI: 0.88-1.35), cough (89.6%; OR = 6.5, CI: 2.16-28.2), and myalgia and dizziness (59.7%; OR = 2.7; CI: 1.36-5.85). Moreover, coinfection was observed in 12 (11.5%) specimens. SARS-CoV-2 and influenza A were the most cooccurring infections, accounting for 33.3% of all positive cases. This study demonstrates cases of COVID-19 infections cooccurring with other acute respiratory infections in Bukavu city during the ongoing outbreak of COVID-19. Therefore, testing for respiratory viruses should be performed in all patients with flu-like symptoms for effective surveillance of the transmission patterns in the COVID-19 affected areas for optimal treatment and effective disease management.

Does economic shocks influence household's healthcare expenditure? Evidence from rural Nigeria.

Health is profoundly influenced by several factors outside the traditional realm of healthcare. This paper employed a two-step Heckman selectivity model to examine factors influencing the decision to spend on health and the effects of economic shocks on health expenditure. The results from the first stage shows that the likelihood of spending on health increased with age, education, income, and decreases if the household is living in the northern region of Nigeria and uses mosquito bed-net. The findings from the second stage estimation show that a fall in the price of food items, an increase in the price of inputs for household enterprises and loss of job are the significant shocks that affect household health expenditure. Based on these findings, this study concluded that fall in the prices of major food items consumed within the household increased income available for health care among the farmers. Going forward, the study recommends the provision of holistic health-economic-welfare interventions for the marginalized rural populace in Nigeria.