This paper highlights the major challenges and considerations for addressing COVID-19 in informal settlements. It discusses what is known about vulnerabilities and how to support local protective action. There is heightened concern about informal urban settlements because of the combination of population density and inadequate access to water and sanitation, which makes standard advice about social distancing and washing hands implausible. There are further challenges to do with the lack of reliable data and the social, political and economic contexts in each setting that will influence vulnerability and possibilities for action. The potential health impacts of COVID-19 are immense in informal settlements, but if control measures are poorly executed these could also have severe negative impacts. Public health interventions must be balanced with social and economic interventions, especially in relation to the informal economy upon which many poor urban residents depend. Local residents, leaders and community-based groups must be engaged and resourced to develop locally appropriate control strategies, in partnership with local governments and authorities. Historically, informal settlements and their residents have been stigmatized, blamed, and subjected to rules and regulations that are unaffordable or unfeasible to adhere to. Responses to COVID-19 should not repeat these mistakes. Priorities for enabling effective control measures include: collaborating with local residents who have unsurpassed knowledge of relevant spatial and social infrastructures, strengthening coordination with local governments, and investing in improved data for monitoring the response in informal settlements.

BackgroundProgress toward reducing the malaria burden in Africa has been measured, or modeled, using datasets with relatively short time-windows. These restricted temporal analyses may miss the wider context of longer-term cycles of malaria risk and hence may lead to incorrect inferences regarding the impact of intervention.Methods1147 age-corrected Plasmodium falciparum parasite prevalence (PfPR2-10) surveys among rural communities along the Kenyan coast were assembled from 1974 to 2014. A Bayesian conditional autoregressive generalized linear mixed model was used to interpolate to 279 small areas for each of the 41 years since 1974. Best-fit polynomial splined curves of changing PfPR2-10 were compared to a sequence of plausible explanatory variables related to rainfall, drug resistance and insecticide-treated bed net (ITN) use.Results P. falciparum parasite prevalence initially rose from 1974 to 1987, dipped in 1991–92 but remained high until 1998. From 1998 onwards prevalence began to decline until 2011, then began to rise through to 2014. This major decline occurred before ITNs were widely distributed and variation in rainfall coincided with some, but not all, short-term transmission cycles. Emerging resistance to chloroquine and introduction of sulfadoxine/pyrimethamine provided plausible explanations for the rise and fall of malaria transmission along the Kenyan coast.ConclusionsProgress towards elimination might not be as predictable as we would like, where natural and extrinsic cycles of transmission confound evaluations of the effect of interventions. Deciding where a country lies on an elimination pathway requires careful empiric observation of the long-term epidemiology of malaria transmission.

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BackgroundSeasonal malaria chemoprevention (SMC) has been shown to be highly efficacious against clinical malaria in areas where transmission is acutely seasonal. SMC targeting depends on a complex interplay of climate, malaria transmission and population distribution. In this study a spatial decision support framework was developed to identify health districts suitable for the targeting of SMC across seven Sahelian countries and northern states of Nigeria that are members of the Nouakchott Initiative.MethodsA spatially explicit decision support framework that links information on seasonality, age-structured population, urbanization, malaria endemicity and the length of transmission season was developed to inform SMC targeting in health districts. Thresholds of seasonality, population and receptive risks were defined to delineate SMC suitable health districts and define the age range of children for targeting. Numbers of children were then computed for the period 2015–2020 in SMC districts. For 2015, this was combined with maps of length of malaria transmission seasons and WHO recommended treatment regimen to quantify the number of tablets required across the SMC health districts.ResultsA total of 597 Sahelian health districts were mapped, out of which 478 (80.1%) were considered suitable for SMC based on seasonality and endemicity thresholds. These districts had an estimated 119.8 million (85%) of the total population in 2015. In the six years from 2015–2020, it is estimated that a total of 158 million children 3m to <5 years, 121 million of whom were in rural areas, will need SMC to achieve universal coverage in the Sahel. If the upper age limit of SMC targeted children was increased to <10 years in low transmission districts, a total 177 million overall, of whom 135 million were rural children, will require chemoprevention in 2015–2020. In 2015 alone, an estimated 49–72 million SP tablets and 148–217 million AQ tablets will be needed to cover all or rural children respectively under the different scenarios of upper age limits.ConclusionsOur proposed framework provides a standardised approach to support targeting and scale up of SMC by the countries of the Nouakchott Initiative. Our analysis suggests that the vast majority of the population in this region are likely to benefit from SMC and substantial resources will be required to reach universal coverage each year.

IntroductionSeveral studies have shown that residents of urban informal settlements/slums are usually excluded and marginalised from formal social systems and structures of power leading to disproportionally worse health outcomes compared to other urban dwellers. To promote health equity for slum dwellers, requires an understanding of how their lived realities shape inequities especially for young children 0–4 years old (ie, under-fives) who tend to have a higher mortality compared with non-slum children. In these proposed studies, we aim to examine how key Social Determinants of Health (SDoH) factors at child and household levels combine to affect under-five health conditions, who live in slums in Bangladesh and Kenya through an intersectionality lens.Methods and analysisThe protocol describes how we will analyse data from the Nairobi Cross-sectional Slum Survey (NCSS 2012) for Kenya and the Urban Health Survey (UHS 2013) for Bangladesh to explore how SDoH influence under-five health outcomes in slums within an intersectionality framework. The NCSS 2012 and UHS 2013 samples will consist of 2199 and 3173 under-fives, respectively. We will apply Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy approach. Some of SDoH characteristics to be considered will include those of children, head of household, mothers and social structure characteristics of household. The primary outcomes will be whether a child had diarrhoea, cough, fever and acute respiratory infection (ARI) 2 weeks preceding surveys.Ethics and disseminationThe results will be disseminated in international peer-reviewed journals and presented in events organised by the Accountability and Responsiveness in Informal Settlements for Equity consortium and international conferences. Ethical approval was not required for these studies. Access to the NCSS 2012 has been given by Africa Population and Health Center and UHS 2013 is freely available.

Rehm et al. highlight the ongoing difficulties in accurately estimating alcohol consumption using surveys. Population surveys, in particular, suffer from non‐response and sampling bias, which affects their representativeness, but they are one of the few ways of estimating differences in consumption across population subgroups. In this article, we highlight different approaches that have been taken in Scotland to try to overcome these problems, from the pragmatic to the sophisticated.

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As citizens around the world become ever more reluctant to respond to survey interview requests, incentives are playing an increasingly important role in maintaining response rates. In face-to-face surveys, interviewers are the key conduit of information about the existence and level of any incentive offered and, therefore, potentially moderate the effectiveness with which an incentive translates nonproductive addresses into interviews. Yet, while the existing literature on the effects of incentives on response rates is substantial, little is currently known about the role of interviewers in determining whether or not incentives are effective. In this article, we apply multilevel models to three different face-to-face interview surveys from the United Kingdom, which vary in their sample designs and incentive levels, to assess whether some interviewers are more successful than others in using incentives to leverage cooperation. Additionally, we link the response outcome data to measures of interviewer characteristics to investigate whether interviewer variability on this dimension is systematically related to level of experience and demographic characteristics. Our results show significant and substantial variability between interviewers in the effectiveness of monetary incentives on the probability of cooperation across all three surveys. However, none of the interviewer characteristics considered are significantly associated with more or less successful interviewers.