ABSTRACT
BACKGROUND: In low- and middle-income countries countries, millions of deaths occur annually from household air pollution (HAP), pulmonary tuberculosis (PTB), and HIV-infection. However, it is unknown whether HAP influences PTB risk among people living with HIV-infection. METHODS: We conducted a case-control study among 1,277 HIV-infected adults in Bukavu, eastern Democratic Republic of Congo (February 2018 - March 2019). Cases had current or recent (<5y) PTB (positive sputum smear or Xpert MTB/RIF), controls had no PTB. Daily and lifetime HAP exposure were assessed by questionnaire and, in a random sub-sample (n=270), by 24-hour measurements of personal carbon monoxide (CO) at home. We used multivariable logistic regression to examine the associations between HAP and PTB. RESULTS: We recruited 435 cases and 842 controls (median age 41 years, [IQR] 33-50; 76% female). Cases were more likely to be female than male (63% vs 37%). Participants reporting cooking for >3h/day and ≥2 times/day and ≥5 days/week were more likely to have PTB (aOR 1·36; 95%CI 1·06-1·75) than those spending less time in the kitchen. Time-weighted average 24h personal CO exposure was related dose-dependently with the likelihood of having PTB, with aOR 4·64 (95%CI 1·1-20·7) for the highest quintile [12·3-76·2 ppm] compared to the lowest quintile [0·1-1·9 ppm]. CONCLUSION: Time spent cooking and personal CO exposure were independently associated with increased risk of PTB among people living with HIV. Considering the high burden of TB-HIV coinfection in the region, effective interventions are required to decrease HAP exposure caused by cooking with biomass among people living with HIV, especially women.
Subject(s)
Air Pollution, Indoor , Air Pollution , HIV Infections , Tuberculosis, Pulmonary , Adult , Humans , Male , Female , Case-Control Studies , HIV Infections/epidemiology , Tuberculosis, Pulmonary/epidemiology , Air Pollution, Indoor/adverse effectsABSTRACT
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.
ABSTRACT
OBJECTIVES: Healthcare workers (HCWs) are on the frontline of combating COVID-19, hence are at elevated risk of contracting an infection with SARS-CoV-2. The present study aims to measure the impact of SARS-CoV-2 on HCWs in central sub-Saharan Africa. SETTING: A cross-sectional serological study was conducted at six urban and five rural hospitals during the first pandemic wave in the South Kivu province, Democratic Republic of the Congo (DRC). PARTICIPANTS: Serum specimens from 1029 HCWs employed during the first pandemic wave were collected between August and October 2020, and data on demographics and work-related factors were recorded during structured interviews. PRIMARY AND SECONDARY OUTCOME MEASURES: The presence of IgG antibodies against SARS-CoV-2 was examined by ELISA. Positive specimens were further tested using a micro-neutralisation assay. Factors driving SARS-CoV-2 seropositivity were assessed by multivariable analysis. RESULTS: Overall SARS-CoV-2 seroprevalence was high among HCWs (33.1%), and significantly higher in urban (41.5%) compared with rural (19.8%) hospitals. Having had presented with COVID-19-like symptoms before was a strong predictor of seropositivity (31.5%). Personal protective equipment (PPE, 88.1% and 11.9%) and alcohol-based hand sanitizer (71.1% and 28.9%) were more often available, and hand hygiene was more often reported after patient contact (63.0% and 37.0%) in urban compared with rural hospitals, respectively. This may suggest that higher exposure during non-work times in high incidence urban areas counteracts higher work protection levels of HCWs. CONCLUSIONS: High SARS-CoV-2 seropositivity indicates widespread transmission of the virus in this region of DRC. Given the absence of publicly reported cases during the same time period at the rural sites, serological studies are very relevant in revealing infection dynamics especially in regions with low diagnostic capacities. This, and discrepancies in the application of PPE between urban and rural sites, should be considered in future pandemic response programmes.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , COVID-19/epidemiology , Cross-Sectional Studies , Democratic Republic of the Congo/epidemiology , Seroepidemiologic Studies , Antibodies, Viral , Health Personnel , Hospitals, RuralABSTRACT
Background: In developing countries, millions of deaths occur annually from household air pollution (HAP), pulmonary tuberculosis (PTB), and HIV-infection. However, it is unknown whether HAP influences PTB risk among people living with HIV-infection. Methods: We conducted a case-control study among 1,277 HIV-infected adults in Bukavu, eastern Democratic Republic of Congo (February 2018 - March 2019). Cases had current or recent (<5y) PTB (positive sputum smear or Xpert MTB/RIF), controls had no PTB. Daily and lifetime HAP exposure were assessed by questionnaire and, in a random sub-sample (n=270), by 24-hour measurements of personal carbon monoxide (CO) at home. We used multivariable logistic regression to examine the associations between HAP and PTB. Results: We recruited 435 cases and 842 controls (median age 41 years, [IQR] 33-50; 76% female). Cases were more likely to be female than male (63% vs 37%). Participants reporting cooking for >3h/day and ≥2 times/day and ≥5 days/weekwere more likely to have PTB (aOR 1·36; 95%CI 1·06-1·75) than those spending less time in the kitchen. Time-weighted average 24h personal CO exposure was related dose-dependently with the likelihood of having PTB, with aOR 4·64 (95%CI 1·1-20·7) for the highest quintile [12·3-76·2 ppm] compared to the lowest quintile [0·1-1·9 ppm]. Conclusion: Time spent cooking and personal CO exposure were independently associated with increased risk of PTB among people living with HIV. Considering the high burden of TB-HIV coinfection in the region, effective interventions are required to decrease HAP exposure caused by cooking with biomass among people living with HIV, especially women.
ABSTRACT
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.