Antimicrobial resistance (AMR) is a global public health threat. Emergence of AMR occurs naturally, but can also be selected for by antimicrobial exposure in clinical and veterinary medicine. Despite growing worldwide attention to AMR, there are substantial limitations in our understanding of the burden, distribution and determinants of AMR at the population level. We highlight the importance of population-based approaches to assess the association between antimicrobial use and AMR in humans and animals. Such approaches are needed to improve our understanding of the development and spread of AMR in order to inform strategies for the prevention, detection and management of AMR, and to support the sustainable use of antimicrobials in healthcare.

IntroductionHealth insurance has been found to increase healthcare utilisation and reduce catastrophic health expenditures in a number of countries; however, coverage is often unequally distributed among populations. The sociodemographic patterns of health insurance in Namibia are not fully understood. We aimed to assess the prevalence of health insurance, the relation between health insurance and health service utilisation and to explore the sociodemographic factors associated with health insurance in Namibia. Such findings may help to inform health policy to improve financial access to healthcare in the country.MethodsUsing data on 14,443 individuals, aged 15 to 64 years, from the 2013 Namibia Demographic and Health Survey, the association between health insurance and health service utilisation was investigated using multivariable mixed effects Poisson regression analyses, adjusted for sociodemographic covariates and regional, enumeration area and household clustering. Multivariable mixed effects Poisson regression analyses were also conducted to explore the association between key sociodemographic factors and health insurance, adjusted for covariates and clustering. Effect modification by sex, education level and wealth quintile was also explored.ResultsJust 17.5% of this population were insured (men: 20.2%; women: 16.2%). In fully-adjusted analyses, education was significantly positively associated with health insurance, independent of other sociodemographic factors (higher education RR: 3.98; 95% CI: 3.11–5.10; p < 0.001). Female sex (RR: 0.83; 95% CI: 0.74–0.94; p = 0.003) and wealth (highest wealth quintile RR: 13.47; 95% CI: 9.06–20.04; p < 0.001) were also independently associated with insurance. There was a complex interaction between sex, education and wealth in the context of health insurance. With increasing education level, women were more likely to be insured (p for interaction < 0.001), and education had a greater impact on the likelihood of health insurance in lower wealth quintiles.ConclusionsIn this population, health insurance was associated with health service utilisation but insurance coverage was low, and was independently associated with sex, education and wealth. Education may play a key role in health insurance coverage, especially for women and the less wealthy. These findings may help to inform the targeting of strategies to improve financial protection from healthcare-associated costs in Namibia.Electronic supplementary materialThe online version of this article (10.1186/s12939-019-0915-4) contains supplementary material, which is available to authorized users.

BackgroundAchieving vector control targets is a key step towards malaria elimination. Because of variations in reporting of progress towards vector control targets in 2013, the coverage of these vector control interventions in Namibia was assessed.MethodsData on 9846 households, representing 41,314 people, collected in the 2013 nationally-representative Namibia Demographic and Health Survey were used to explore the coverage of two vector control methods: indoor residual spraying (IRS) and insecticide-treated nets (ITNs). Regional data on Plasmodium falciparum parasite rate in those aged 2–10 years (PfPR2–10), obtained from the Malaria Atlas Project, were used to provide information on malaria transmission intensity. Poisson regression analyses were carried out exploring the relationship between household interventions and PfPR2–10, with fully adjusted models adjusting for wealth and residence type and accounting for regional and enumeration area clustering. Additionally, the coverage as a function of government intervention zones was explored and models were compared using log-likelihood ratio tests.ResultsIntervention coverage was greatest in the highest transmission areas (PfPR2–10 ≥ 5%), but was still below target levels of 95% coverage in these regions, with 27.6% of households covered by IRS, 32.3% with an ITN and 49.0% with at least one intervention (ITN and/or IRS). In fully adjusted models, PfPR2–10 ≥ 5% was strongly associated with IRS (RR 14.54; 95% CI 5.56–38.02; p < 0.001), ITN ownership (RR 5.70; 95% CI 2.84–11.45; p < 0.001) and ITN and/or IRS coverage (RR 5.32; 95% CI 3.09–9.16; p < 0.001).ConclusionsThe prevalence of IRS and ITN interventions in 2013 did not reflect the Namibian government intervention targets. As such, there is a need to include quantitative monitoring of such interventions to reliably inform intervention strategies for malaria elimination in Namibia.Electronic supplementary materialThe online version of this article (10.1186/s12936-018-2417-z) contains supplementary material, which is available to authorized users.