Acceptability and Predictors of Uptake of Anti-retroviral Pre-exposure Prophylaxis (PrEP) Among Fishing Communities in Uganda: A Cross-Sectional Discrete Choice Experiment Survey.

We used a discrete choice experiment to assess the acceptability and potential uptake of HIV pre-exposure prophylaxis (PrEP) among 713 HIV-negative members of fishing communities in Uganda. Participants were asked to choose between oral pill, injection, implant, condoms, vaginal ring (women), and men circumcision. Product attributes were HIV prevention effectiveness, sexually transmitted infection (STI) prevention, contraception, waiting time, and secrecy of use. Data were analysed using mixed multinomial logit and latent class models. HIV prevention effectiveness was viewed as the most important attribute. Both genders preferred oral PrEP. Women least preferred the vaginal ring and men the implant. Condom use was predicted to decrease by one third among men, and not to change amongst women. Oral PrEP and other new prevention technologies are acceptable among fishing communities and may have substantial demand. Future work should explore utility of multiple product technologies that combine contraception with HIV and other STI prevention

The general population cohort in rural south-western Uganda: a platform for communicable and non-communicable disease studies.

The General Population Cohort (GPC) was set up in 1989 to examine trends in HIV prevalence and incidence, and their determinants in rural south-western Uganda. Recently, the research questions have included the epidemiology and genetics of communicable and non-communicable diseases (NCDs) to address the limited data on the burden and risk factors for NCDs in sub-Saharan Africa. The cohort comprises all residents (52% aged ≥13years, men and women in equal proportions) within one-half of a rural sub-county, residing in scattered houses, and largely farmers of three major ethnic groups. Data collected through annual surveys include; mapping for spatial analysis and participant location; census for individual socio-demographic and household socioeconomic status assessment; and a medical survey for health, lifestyle and biophysical and blood measurements to ascertain disease outcomes and risk factors for selected participants. This cohort offers a rich platform to investigate the interplay between communicable diseases and NCDs. There is robust infrastructure for data management, sample processing and storage, and diverse expertise in epidemiology, social and basic sciences. For any data access enquiries you may contact the director, MRC/UVRI, Uganda Research Unit on AIDS by email to [email protected] or the corresponding author

Estimating Incidence from Prevalence in Generalised HIV Epidemics: Methods and Validation

Timothy Hallett and colleagues develop and test two user-friendly methods to estimate HIV incidence based on changes in cross-sectional prevalence, using either mortality rates or survival after infection

Model-based small area estimation methods and precise district-level HIV prevalence estimates in Uganda

Background Model-based small area estimation methods can help generate parameter estimates at the district level, where planned population survey sample sizes are not large enough to support direct estimates of HIV prevalence with adequate precision. We computed district-level HIV prevalence estimates and their 95% confidence intervals for districts in Uganda. Methods Our analysis used direct survey and model-based estimation methods, including Fay-Herriot (area-level) and Battese-Harter-Fuller (unit-level) small area models. We used regression analysis to assess for consistency in estimating HIV prevalence. We use a ratio analysis of the mean square error and the coefficient of variation of the estimates to evaluate precision. The models were applied to Uganda Population-Based HIV Impact Assessment 2016/2017 data with auxiliary information from the 2016 Lot Quality Assurance Sampling survey and antenatal care data from district health information system datasets for unit-level and area level models, respectively. Results Estimates from the model-based and the direct survey methods were similar. However, direct survey estimates were unstable compared with the model-based estimates. Area level model estimates were more stable than unit-level model estimates. The correlation between unit-level and direct survey estimates was (β1 = 0.66, r2 = 0.862), and correlation between area-level model and direct survey estimates was (β1 = 0.44, r2 = 0.698). The error associated with the estimates decreased by 37.5% and 33.1% for the unit-level and arealevel models, respectively, compared to the direct survey estimates. Conclusions Although the unit-level model estimates were less precise than the area-level model estimates, they were highly correlated with the direct survey estimates and had less standard error associated with estimates than the area-level model. Unit-level models provide more accurate and reliable data to support local decision-making when unit-level auxiliary information is available

Age-specific mortality patterns in HIV-infected individuals: a comparative analysis of African community study data

Objectives: Describe age-specific mortality patterns of HIV-infected adults in African communities before introduction of HAART. Methods: Mortality data (deaths and person-years observed) for HIV-positive subjects aged 15–65 from six African community studies in five different countries were pooled, combining information from 1793 seroconverters and 8534 HIV positive when first tested. Age-specific mortality hazards were modelled using parametric regression based on the Weibull distribution, to investigate effects of sex, and site-specific measures of mean age at incidence, crude mortality rate of uninfected, and measures of epidemic maturity. Results: The combined studies yielded a total of 31 777 person-years of observation for HIV-positive subjects, during which time 2602 deaths were recorded. Mortality rates rose almost linearly with age, from below 50/1000 at ages < 20 years, up to 150/1000 at 50 years +. There was no significant difference between men and women in level or age pattern of mortality. Weibull regression analysis suggested that intersite variation could be explained by HIV prevalence trend, and by the ratio of HIV proportional mortality to current HIV prevalence. A model representation was constructed with a common age pattern of mortality, but allowing the level to be adjusted by specifying HIV prevalence indicators. Conclusion: The linear age trend of mortality in HIV-infected populations was satisfactorily represented by a Weibull function providing a parametric model adaptable for representing different levels of HIV-related mortality. This model might be simpler to use in demographic projections of HIV-affected populations than models based on survival post-infection

Social media use and COVID-19 vaccine status among a nationally representative population sample in Uganda

Objectives The effect of social media on COVID-19 vaccination behavior is sub-Saharan Africa is unclear. We conducted a study to determine social media use among a random nationally representative sample of adults in Uganda and assessed the association between recent social media use and COVID-19 vaccination uptake. Methods We used data from the 2020 general population survey in Uganda, the Population-based HIV Impact Assessment Survey, to identify a probability sample for a mobile phone survey and included nonphone owners in the phone survey by asking phone owners to pass the phone. Results In March 2022, of the 1022 survey participants, 213 (20%) did not own a mobile phone, 842 (80%) owned a mobile phone, of whom 199 (24%) indicated social media use, and 643 (76%) of whom did not use social media. Among all participants, the most frequent source of COVID-19 vaccine information was radio. Overall, 62% reported receiving the COVID-19 vaccination. The multivariable logistic regression model found that social media use was not associated with vaccination status. Conclusion Social media users in this population sample from Uganda—who were mainly young, urban residents with higher educational attainment—continue to utilize TV, radio and health care workers for public health messages, thus the Government of Uganda should continue to conduct public health communication through these mediums

Quantifying HIV-1 transmission due to contaminated injections

Assessments of the importance of different routes of HIV-1 (HIV) transmission are vital for prioritization of control efforts. Lack of consistent direct data and large uncertainty in the risk of HIV transmission from HIV-contaminated injections has made quantifying the proportion of transmission caused by contaminated injections in sub-Saharan Africa difficult and unavoidably subjective. Depending on the risk assumed, estimates have ranged from 2.5% to 30% or more. We present a method based on an age-structured transmission model that allows the relative contribution of HIV-contaminated injections, and other routes of HIV transmission, to be robustly estimated, both fully quantifying and substantially reducing the associated uncertainty. To do this, we adopt a Bayesian perspective, and show how prior beliefs regarding the safety of injections and the proportion of HIV incidence due to contaminated injections should, in many cases, be substantially modified in light of age-stratified incidence and injection data, resulting in improved (posterior) estimates. Applying the method to data from rural southwest Uganda, we show that the highest estimates of the proportion of incidence due to injections are reduced from 15.5% (95% credible interval) (0.7%, 44.9%) to 5.2% (0.5%, 17.0%) if random mixing is assumed, and from 14.6% (0.7%, 42.5%) to 11.8% (1.2%, 32.5%) under assortative mixing. Lower, and more widely accepted, estimates remain largely unchanged, between 1% and 3% (0.1–6.3%). Although important uncertainty remains, our analysis shows that in rural Uganda, contaminated injections are unlikely to account for a large proportion of HIV incidence. This result is likely to be generalizable to many other populations in sub-Saharan Africa

Additional file 1: of Global health leadership training in resource-limited settings: a collaborative approach by academic institutions and local health care programs in Uganda

Afya Bora fellowship skills log book. Fellows completed the skills logbook to indicate all the skills acquired from both the didactic modules and the attachment site period

Estimating 'net' HIV-related mortality and the importance of background mortality rates.

OBJECTIVES: To estimate mortality directly attributable to HIV in HIV-infected adults in low and middle income countries and discuss appropriate methodology. DESIGN: : Illustrative analysis of pooled data from six studies across sub-Saharan Africa and Thailand with data on individuals with known dates of seroconversion to HIV. METHODS: Five of the studies also had data from HIV-negative subjects and one had verbal autopsies. Data for HIV-negative cohorts were weighted by the initial age and sex distribution of the seroconverters. Using the survival of the HIV-negative group to represent the background mortality, net survival from HIV was calculated for the seroconverters using competing risk methods. Mortality from all causes and 'net' mortality were modelled using piecewise exponential regression. Alternative approaches are explored in the dataset without information on mortality of uninfected individuals. RESULTS: The overall effect of the net mortality adjustment was to increase survivorship proportionately by 2 to 5% at 6 years post-infection. The increase ranged from 2% at ages 15-24 to 22% in those 55 and over. Mortality rate ratios between sites were similar to corresponding ratios for all-cause mortality. CONCLUSION: Differences between HIV mortality in different populations and age groups are not explained by differences in background mortality, although this does appear to contribute to the excess at older ages. In the absence of data from uninfected individuals in the same population, model life tables can be used to calculate background rates

Time from HIV seroconversion to death: a collaborative analysis of eight studies in six low and middle-income countries before highly active antiretroviral therapy.

OBJECTIVES: To estimate survival patterns after HIV infection in adults in low and middle-income countries. DESIGN: An analysis of pooled data from eight different studies in six countries. METHODS: HIV seroconverters were included from eight studies (three population-based, two occupational, and three clinic cohorts) if they were at least 15 years of age, and had no more than 4 years between the last HIV-negative and subsequent HIV-positive test. Four strata were defined: East African cohorts; South African miners cohort; Thai cohorts; Haitian clinic cohort. Kaplan-Meier functions were used to estimate survival patterns, and Weibull distributions were used to model and extend survival estimates. Analyses examined the effect of site, age, and sex on survival. RESULTS: From 3823 eligible seroconverters, 1079 deaths were observed in 19 671 person-years of follow-up. Survival times varied by age and by study site. Adjusting to age 25-29 years at seroconversion, the median survival was longer in South African miners: 11.6 years [95% confidence interval (CI) 9.8-13.7] and East African cohorts: 11.1 years (95% CI 8.7-14.2) than in Haiti: 8.3 years (95% CI 3.2-21.4) and Thailand: 7.5 years (95% CI 5.4-10.4). Survival was similar for men and women, after adjustment for age at seroconversion and site. CONCLUSION: Without antiretroviral therapy, overall survival after HIV infection in African cohorts was similar to survival in high-income countries, with a similar pattern of faster progression at older ages at seroconversion. Survival appears to be significantly worse in Thailand where other, unmeasured factors may affect progression