This paper describes the relationship between temperature change and diarrhoea in under five-year-old children in the Cape Town Metropolitan Area (CTMA) of South Africa. The study used climatic and aggregated surveillance diarrhoea incidence data of two peak periods of seven months each over two consecutive years. A Poisson regression model and a lagged Poisson model with autocorrelation was performed to test the relationship between climatic parameters (minimum and maximum temperature) and incidence of diarrhoea. In total, 58,617 cases of diarrhoea occurred in the CTMA, which is equivalent to 8.60 cases per 100 population under five years old for the study period. The mixed effect overdispersed Poisson model showed that a cluster adjusted effect of an increase of 5 °C in minimum and maximum temperature results in a 40% (Incidence risk ratio IRR: 1.39, 95% CI 1.31–1.48) and 32% (IRR: 1.32, 95% CI: 1.22–1.41) increase in incident cases of diarrhoea, respectively, for the two periods studied. Autocorrelation of one-week lag (Autocorrelation AC 1) indicated that a 5 °C increase in minimum and maximum temperature led to 15% (IRR: 1.46, 95% CI: 1.09–1.20) and 6% (IRR: 1.06, 95% CI: 1.01–1.12) increase in diarrhoea cases, respectively. In conclusion, there was an association between an increase in minimum and maximum temperature, and the rate at which diarrhoea affected children under the age of five years old in the Cape Town Metropolitan Area. This finding may have implications for the effects of global warming and requires further investigation.

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Establishing accurate population size estimates (PSE) is important for prioritizing and planning provision of services. Multiple source capture-recapture sampling method increases PSE accuracy and reliability. In August 2018, the three-source capture-recapture (3S-CRC) method was employed with a stringent assumption of sample independence to estimate the number of female sex workers (FSW) in Rwanda. Using Rwanda 2017 FSW hotspots mapping data, street and venue based FSW were sampled at the sector level of each province and tagged with two unique gifts. Each capture was completed within one week to minimize FSW migration between provinces and recall bias. The three captures had 1042, 1204 and 1488 FSW. There were 111 FSW recaptured between captures 1 and 2; 237 between captures 2 and 3; 203 between captures 1 and 3, and 46 captured in all three. The PSE for street and venue based FSW in Rwanda lies within 95% credible set: 8,328-22,806 with corresponding median of 13,716 FSW. The 3S-CRC technique was low-cost and relatively easy to use for PSE in hard-to-reach populations. This estimate provides the basis for determining the denominators to assess HIV program performance towards FSW and epidemic control and warrants further PSE for home-and cyber-based FSW in Rwanda.

Background Despite Rwanda’s progress toward HIV epidemic control, 16.2% of HIV-positive individuals are unaware of their HIV positive status. Tailoring the public health strategy could help reach these individuals with new HIV infection and achieve epidemic control. Recency testing is primarily for surveillance, monitoring, and evaluation but it’s not for diagnostic purposes. However, it’s important to know what proportion of the newly diagnosed are recent infections so that HIV prevention can be tailored to the profile of people who are recently infected. We therefore used available national data to characterize individuals with recent HIV infection in Rwanda to inform the epidemic response. Methods We included all national-level data for recency testing reported from October 2018 to June 2020. Eligible participants were adults (aged ≥15 years) who had a new HIV diagnosis, who self-reported being antiretroviral therapy (ART) naïve, and who had consented to recency testing. Numbers and proportions of recent HIV infections were estimated, and precision around these estimates was calculated with 95% confidence intervals (CI). Logistic regression was used to assess factors associated with being recently (within 12 months) infected with HIV. Results Of 7,785 eligible individuals with a new HIV-positive diagnosis, 475 (6.1%) met the criteria for RITA recent infection. The proportion of RITA recent infections among individuals with newly identified HIV was high among those aged 15–24 years (9.6%) and in men aged ≥65 years (10.3%) compared to other age groups; and were higher among women (6.7%) than men (5.1%). Of all recent cases, 68.8% were women, and 72.2% were aged 15–34 years. The Northern province had the fewest individuals with newly diagnosed HIV but had the highest proportion of recent infections (10.0%) compared to other provinces. Recent infections decreased by 19.6% per unit change in time (measured in months). Patients aged ≥25 years were less likely to have recent infection than those aged 15–24 years with those aged 35–49 years being the least likely to have recent infection compared to those aged 15–24 years (adjusted odds ratio [aOR], 0.415 [95% CI: 0.316–0.544]). Conclusion Public health surveillance targeting the areas and the identified groups with high risk of recent infection could help improve outcomes.