Suchergebnisse

In 2015, Zimbabwe introduced third-line antiretroviral therapy (ART) through four designated treatment centers; three government clinics in Harare and Bulawayo, and Newlands Clinic (NC), operated by a private voluntary organization in Harare. We describe characteristics of patients receiving third line ART and analyzed treatment outcomes in this national programme as of 31 December 2018.

In an effort to reduce firearm mortality rates in the USA, US states have enacted a range of firearm laws to either strengthen or deregulate the existing main federal gun control law, the Brady Law. We set out to determine the independent association of different firearm laws with overall firearm mortality, homicide firearm mortality, and suicide firearm mortality across all US states. We also projected the potential reduction of firearm mortality if the three most strongly associated firearm laws were enacted at the federal level.

Background: The assessment of geographical heterogeneity of HIV among men who have sex with men (MSM) and people who inject drugs (PWID) can usefully inform targeted HIV prevention and care strategies. Objective: We aimed to measure HIV seroprevalence and identify hotspots of HIV infection among MSM and PWID in Nigeria. Methods: We included all MSM and PWID accessing HIV testing services across 7 prioritized states (Lagos, Nasarawa, Akwa Ibom, Cross Rivers, Rivers, Benue, and the Federal Capital Territory) in 3 geographic regions (North Central, South South, and South West) between October 1, 2016, and September 30, 2017. We extracted data from national testing registers, georeferenced all HIV test results aggregated at the local government area level, and calculated HIV seroprevalence. We calculated and compared HIV seroprevalence from our study to the 2014 integrated biological and behavioural surveillance survey and used global spatial autocorrelation and hotspot analysis to highlight patterns of HIV infection and identify areas of significant clustering of HIV cases. Results: MSM and PWID had HIV seroprevalence rates of 12.14% (3209/26,423) and 11.88% (1126/9474), respectively. Global spatial autocorrelation Moran I statistics revealed a clustered distribution of HIV infection among MSM and PWID with a <5% and <1% likelihood that this clustered pattern could be due to chance, respectively. Significant clusters of HIV infection (Getis-Ord-Gi* statistics) confined to the North Central and South South regions were identified among MSM and PWID. Compared to the 2014 integrated biological and behavioural surveillance survey, our results suggest an increased HIV seroprevalence among PWID and a substantial decrease among MSM. Conclusions: This study identified geographical areas to prioritize for control of HIV infection among MSM and PWID, thus demonstrating that geographical information system technology is a useful tool to inform public health planning for interventions targeting epidemic control of HIV infection.

INTRODUCTION There are limited data on paediatric HIV care and treatment programmes in low-resource settings. METHODS A standardized survey was completed by International epidemiologic Databases to Evaluate AIDS paediatric cohort sites in the regions of Asia-Pacific (AP), Central Africa (CA), East Africa (EA), Southern Africa (SA) and West Africa (WA) to understand operational resource availability and paediatric management practices. Data were collected through January 2010 using a secure, web-based software program (REDCap). RESULTS A total of 64,552 children were under care at 63 clinics (AP, N=10; CA, N=4; EA, N=29; SA, N=10; WA, N=10). Most were in urban settings (N=41, 65%) and received funding from governments (N=51, 81%), PEPFAR (N=34, 54%), and/or the Global Fund (N=15, 24%). The majority were combined adult-paediatric clinics (N=36, 57%). Prevention of mother-to-child transmission was integrated at 35 (56%) sites; 89% (N=56) had access to DNA PCR for infant diagnosis. African (N=40/53) but not Asian sites recommended exclusive breastfeeding up until 4-6 months. Regular laboratory monitoring included CD4 (N=60, 95%), and viral load (N=24, 38%). Although 42 (67%) sites had the ability to conduct acid-fast bacilli (AFB) smears, 23 (37%) sites could conduct AFB cultures and 18 (29%) sites could conduct tuberculosis drug susceptibility testing. Loss to follow-up was defined as >3 months of lost contact for 25 (40%) sites, >6 months for 27 sites (43%) and >12 months for 6 sites (10%). Telephone calls (N=52, 83%) and outreach worker home visits to trace children lost to follow-up (N=45, 71%) were common. CONCLUSIONS In general, there was a high level of patient and laboratory monitoring within this multiregional paediatric cohort consortium that will facilitate detailed observational research studies. Practices will continue to be monitored as the WHO/UNAIDS Treatment 2.0 framework is implemented.

AbstractIntroductionWithin many sub‐Saharan African countries including Malawi, HIV prevalence varies widely between regions. This variability may be related to the distribution of population groups with specific sociobehavioural characteristics that influence the transmission of HIV and the uptake of prevention. In this study, we intended to identify groups of people in Malawi with similar risk profiles.MethodsWe used data from the Demographic and Health Survey in Malawi (2015 to 2016), and stratified the analysis by sex. We considered demographic, socio‐behavioural and HIV‐related variables. Using Latent Class Analysis (LCA), we identified groups of people sharing common sociobehavioural characteristics. The optimal number of classes (groups) was selected based on the Bayesian information criterion. We compared the proportions of individuals belonging to the different groups across the three regions and 28 districts of Malawi.ResultsWe found nine groups of women and six groups of men. Most women in the groups with highest risk of being HIV positive were living in female‐headed households and were formerly married or in a union. Among men, older men had the highest risk of being HIV positive, followed by young (20 to 25) single men. Generally, low HIV testing uptake correlated with lower risk of having HIV. However, rural adolescent girls had a low probability of being tested (48.7%) despite a relatively high HIV prevalence. Urban districts and the Southern region had a higher percentage of high‐prevalence and less tested groups of individuals than other areas.ConclusionsLCA is an efficient method to find groups of people sharing common HIV risk profiles, identify particularly vulnerable sub‐populations, and plan targeted interventions focusing on these groups. Tailored support, prevention and HIV testing programmes should focus particularly on female household heads, adolescent girls living in rural areas, older married men and young men who have never been married.

AbstractIntroductionSocio‐behavioural factors may contribute to the wide variance in HIV prevalence between and within sub‐Saharan African (SSA) countries. We studied the associations between socio‐behavioural variables potentially related to the risk of acquiring HIV.MethodsWe used Bayesian network models to study associations between socio‐behavioural variables that may be related to HIV. A Bayesian network consists of nodes representing variables, and edges representing the conditional dependencies between variables. We analysed data from Demographic and Health Surveys conducted in 29 SSA countries between 2010 and 2016. We predefined and dichotomized 12 variables, including factors related to age, literacy, HIV knowledge, HIV testing, domestic violence, sexual activity and women's empowerment. We analysed data on men and women for each country separately and then summarized the results across the countries. We conducted a second analysis including also the individual HIV status in a subset of 23 countries where this information was available. We presented summary graphs showing associations that were present in at least six countries (five in the analysis with HIV status).ResultsWe analysed data from 190,273 men (range across countries 2295 to 17,359) and 420,198 women (6621 to 38,948). The two variables with the highest total number of edges in the summary graphs were literacy and rural/urban location. Literacy was negatively associated with false beliefs about AIDS and, for women, early sexual initiation, in most countries. Literacy was also positively associated with ever being tested for HIV and the belief that women have the right to ask their husband to use condoms if he has a sexually transmitted infection. Rural location was positively associated with false beliefs about HIV and the belief that beating one's wife is justified, and negatively associated with having been tested for HIV. In the analysis including HIV status, being HIV positive was associated with female‐headed household, older age and rural location among women, and with no variables among men.ConclusionsLiteracy and urbanity were strongly associated with several factors that are important for HIV acquisition. Since literacy is one of the few variables that can be improved by interventions, this makes it a promising intervention target.

AbstractIntroductionOutbreaks of hepatitis C virus (HCV) infections among HIV‐positive men who have sex with men (MSM) have been observed globally. Using a multi‐modelling approach we estimate the time and number of direct‐acting antiviral treatment courses required to achieve an 80% reduction in HCV prevalence among HIV‐positive MSM in the state of Victoria, Australia.MethodsThree models of HCV transmission, testing and treatment among MSM were compared: a dynamic compartmental model; an agent‐based model (ABM) parametrized to local surveillance and behavioural data ("ABM1"); and an ABM with a more heterogeneous population ("ABM2") to determine the influence of extreme variations in sexual risk behaviour.ResultsAmong approximately 5000 diagnosed HIV‐positive MSM in Victoria, 10% are co‐infected with HCV. ABM1 estimated that an 80% reduction in HCV prevalence could be achieved in 122 (inter‐quartile range (IQR) 112 to 133) weeks with 523 (IQR 479 to 553) treatments if the average time from HCV diagnosis to treatment was six months. This was reduced to 77 (IQR 69 to 81) weeks if the average time between HCV diagnosis and treatment commencement was decreased to 16 weeks. Estimates were consistent across modelling approaches; however ABM2 produced fewer incident HCV cases, suggesting that treatment‐as‐prevention may be more effective in behaviourally heterogeneous populations.ConclusionsMajor reductions in HCV prevalence can be achieved among HIV‐positive MSM within two years through routine HCV monitoring and prompt treatment as a part of HIV care. Compartmental models constructed with limited behavioural data are likely to produce conservative estimates compared to models of the same setting with more complex parametrizations.

IntroductionLesotho was among the first countries to adopt decentralization of care from hospitals to nurse‐led health centres (HCs) to scale up the provision of antiretroviral therapy (ART). We compared outcomes between patients who started ART at HCs and hospitals in two rural catchment areas in Lesotho.MethodsThe two catchment areas comprise two hospitals and 12 HCs. Patients ≥16 years starting ART at a hospital or HC between 2008 and 2011 were included. Loss to follow‐up (LTFU) was defined as not returning to the facility for ≥180 days after the last visit, no follow‐up (no FUP) as not returning after starting ART, and retention in care as alive and on ART at the facility. The data were analysed using logistic regression, competing risk regression and Kaplan‐Meier methods. Multivariable analyses were adjusted for sex, age, CD4 cell count, World Health Organization stage, catchment area and type of ART. All analyses were stratified by gender.ResultsOf 3747 patients, 2042 (54.5%) started ART at HCs. Both women and men at hospitals had more advanced clinical and immunological stages of disease than those at HCs. Over 5445 patient‐years, 420 died and 475 were LTFU. Kaplan‐Meier estimates for three‐year retention were 68.7 and 69.7% at HCs and hospitals, respectively, among women (p=0.81) and 68.8% at HCs versus 54.7% at hospitals among men (p<0.001). These findings persisted in adjusted analyses, with similar retention at HCs and hospitals among women (odds ratio (OR): 0.89, 95% confidence interval (CI): 0.73–1.09) and higher retention at HCs among men (OR: 1.53, 95% CI: 1.20–1.96). The latter result was mainly driven by a lower proportion of patients LTFU at HCs (OR: 0.68, 95% CI: 0.51–0.93).ConclusionsIn rural Lesotho, overall retention in care did not differ significantly between nurse‐led HCs and hospitals. However, men seemed to benefit most from starting ART at HCs, as they were more likely to remain in care in these facilities compared to hospitals.

This study analyzed the reported incidence of COVID-19 and associated epidemiological and socio-economic factors in the WHO African region. Data from COVID-19 confirmed cases and SARS-CoV-2 tests reported to the WHO by Member States between 25 February and 31 December 2020 and publicly available health and socio-economic data were analyzed using univariate and multivariate binomial regression models. The overall cumulative incidence was 1846 cases per million population. Cape Verde (21350 per million), South Africa (18060 per million), Namibia (9840 per million), Eswatini (8151 per million) and Botswana (6044 per million) recorded the highest cumulative incidence, while Benin (260 per million), Democratic Republic of Congo (203 per million), Niger (141 cases per million), Chad (133 per million) and Burundi (62 per million) recorded the lowest. Increasing percentage of urban population (beta=-0.011, p=0.04) was associated with low cumulative incidence, while increasing number of cumulative SARS-CoV-2 tests performed per 10000 population (beta=0.0006, p=0.006) and proportion of population aged 15-64 years (adjusted beta=0.174, p<0.0001) were associated with high COVID-19 cumulative incidence. With limited testing capacities and overwhelmed health systems, these findings highlight the need for countries to increase and decentralize testing capacities and adjust testing strategies to target most at-risk populations.