Face mask mandates and risk compensation: an analysis of mobility data during the COVID-19 pandemic in Bangladesh

IntroductionConcerns have been raised about the potential for risk compensation in the context of mask mandates for mitigating the spread of COVID-19. However, the debate about the presence or absence of risk compensation for universal mandatory mask-wearing rules—especially in the context of COVID-19—is not settled yet.MethodsMobility is used as a proxy for risky behaviour before and after the mask mandates. Two sets of regressions are estimated to decipher (any) risk-compensating effect of mask mandate in Bangladesh. These include: (1) intervention regression analysis of daily activities at six types of locations, using pre-mask-mandate and post-mandate data; and (2) multiple regression analysis of daily new COVID-19 cases on daily mobility (lagged) to establish mobility as a valid proxy.Results(1) Statistically, mobility increased at all five non-residential locations, while home stays decreased after the mask mandate was issued; (2) daily mobility had a statistically significant association on daily new cases (with around 10 days of lag). Both significances were calculated at 95% confidence level.ConclusionCommunity mobility had increased (and stay at home decreased) after the mandatory mask-wearing rule, and given mobility is associated with increases in new COVID-19 cases, there is evidence of risk compensation effect of the mask mandate—at least partially—in Bangladesh.

A growing disadvantage of being born in an urban area? Analysing urban–rural disparities in neonatal mortality in 21 African countries with a focus on Tanzania

IntroductionNeonatal mortality rate (NMR) has been declining in sub-Saharan African (SSA) countries, where historically rural areas had higher NMR compared with urban. The 2015–2016 Demographic and Health Survey (DHS) in Tanzania showed an exacerbation of an existing pattern with significantly higher NMR in urban areas. The objective of this study is to understand this disparity in SSA countries and examine the specific factors potentially underlying this association in Tanzania.MethodsWe assessed urban–rural NMR disparities among 21 SSA countries with four or more DHS, at least one of which was before 2000, using the DHS StatCompiler. For Tanzania DHS 2015–2016, descriptive statistics were carried out disaggregated by urban and rural areas, followed by bivariate and multivariable logistic regression modelling the association between urban/rural residence and neonatal mortality, adjusting for other risk factors.ResultsAmong 21 countries analysed, Tanzania was the only SSA country where urban NMR (38 per 1000 live births) was significantly higher than rural (20 per 1,000), with largest difference during first week of life. We analysed NMR on the 2015–2016 Tanzania DHS, including live births to 9736 women aged between 15 and 49 years. Several factors were significantly associated with higher NMR, including multiplicity of pregnancy, being the first child, higher maternal education, and male child sex. However, their inclusion did not attenuate the effect of urban–rural differences in NMR. In multivariable models, urban residence remained associated with double the odds of neonatal mortality compared with rural.ConclusionThere is an urgent need to understand the role of quality of facility-based care, including role of infections, and health-seeking behaviour in case of neonatal illness at home. However, additional factors might also be implicated and higher NMR within urban areas of Tanzania may signal a shift in the pattern of neonatal mortality across several other SSA countries.

Co-learning during the co-creation of a dengue early warning system for the health sector in Barbados

Over the past decade, the Caribbean region has been challenged by compound climate and health hazards, including tropical storms, extreme heat and droughts and overlapping epidemics of mosquito-borne diseases, including dengue, chikungunya and Zika. Early warning systems (EWS) are a key climate change adaptation strategy for the health sector. An EWS can integrate climate information in forecasting models to predict the risk of disease outbreaks several weeks or months in advance. In this article, we share our experiences of co-learning during the process of co-creating a dengue EWS for the health sector in Barbados, and we discuss barriers to implementation as well as key opportunities. This process has involved bringing together health and climate practitioners with transdisciplinary researchers to jointly identify needs and priorities, assess available data, co-create an early warning tool, gather feedback via national and regional consultations and conduct trainings. Implementation is ongoing and our team continues to be committed to a long-term process of collaboration. Developing strong partnerships, particularly between the climate and health sectors in Barbados, has been a critical part of the research and development. In many countries, the national climate and health sectors have not worked together in a sustained or formal manner. This collaborative process has purposefully pushed us out of our comfort zone, challenging us to venture beyond our institutional and disciplinary silos. Through the co-creation of the EWS, we anticipate that the Barbados health system will be better able to mainstream climate information into decision-making processes using tailored tools, such as epidemic forecast reports, risk maps and climate-health bulletins, ultimately increasing the resilience of the health system.

The impact of the COVID-19 pandemic on the incidence and mortality of zoonotic diseases in China

BackgroundIt has been reported that strict non-pharmaceutical measures can significantly reduce the incidence and mortality of respiratory and intestinal infectious diseases during the COVID-19 pandemic, but there are limited reports on the impact in terms of the rates of zoonotic diseases.MethodsWe extracted the incidence and mortality data of eight notifiable infectious zoonotic diseases from the website of the National Health Commission of the People’s Republic of China for the period of January 2015 to April 2021.ResultsFirst, the overall incidence of zoonotic diseases decreased from 0.3714 per 100 000 in 2015–2019 to 0.2756 in 2020 (25.79% reduction, p<0.001); however, a dramatic increase in activity was seen in 2021 compared with 2020 (0.4478 per 100 000 in 2021, 62.47% increase, p<0.001). Anthrax, brucellosis, leptospirosis and hydatid disease exhibited significant upward trends in 2021. Second, analysed further by stages, the monthly incidence in the routine stage (from May to December 2020) was much higher than that in the emergency stage of the COVID-19 (from January to April 2020) (55.33% increase, p<0.001). We also found that the monthly observed incidence was significantly lower than the predicted incidence of a 10.29% reduction in the emergency stage. Third, no differences were seen in mortality between 2021 and 2020, while a significant decline was found in 2020 compared with the previous 5 years (72.70%, p<0.001).ConclusionsStrict containment and feasible suppression strategies during the 2020 period of the COVID-19 pandemic had positive impacts on the overall incidence of zoonotic diseases in China. However, anthrax, brucellosis, leptospirosis and hydatid diseases might increase with the relaxation of non-pharmacological interventions in 2021.

‘Where are the dead flies!’: perceptions of local communities towards the deployment of Tiny Targets to control tsetse in the Democratic Republic of the Congo

The National Programme for the control of human African trypanosomiasis in Democratic Republic of Congo includes a large-scale vector control operation using Tiny Targets. These are small panels of insecticide-impregnated cloth that are deployed in riverine habitat where tsetse flies concentrate. The effectiveness of Tiny Targets depends partly on acceptance by local communities. In 2018, we conducted research to explore the perception and acceptability of Tiny Targets in two different village clusters where Tiny Targets had been deployed by the local community or external teams. We conducted fourteen focus group discussions and seven semistructured interviews in three villages from each cluster in the Yasa Bonga health zone. Our findings showed that acceptability was better in the cluster where communities were involved in the deployment of Tiny Targets. Also in this cluster, awareness about Tiny Targets was satisfactory and the project was implemented within local customs, which promoted a positive perception of Tiny Targets and their benefits. In the cluster where external teams deployed Tiny Targets, a lack of information and communication, stereotypes applied by communities towards the deployment teams and the impression of inadequate respect for local customs led to anxiety and a misleading interpretation of the purpose of Tiny Targets and negatively influenced acceptability. This study highlights the importance of involving communities for programme acceptance. Our research underlined how awareness campaigns and communication are essential, but also how working within the scope of community social norms and customs are equally important. Prospects for the successful use of Tiny Targets are greater when communities are involved because the use can be adapted to social norms.

Using social network analysis to understand multisectoral governance in district-level tobacco control programme implementation in India

IntroductionInterest in multisectoral policies has increased, particularly in the context of low-income and middle-income countries and efforts towards Sustainable Development Goals, with greater attention to understand effective strategies for implementation and governance. The study aimed to explore and map the composition and structure of a multisectoral initiative in tobacco control, identifying key factors engaged in policy implementation and their patterns of relationships in local-level networks in two districts in the state of Karnataka, India.MethodsSocial network analysis (SNA) was used to examine the structure of two district tobacco control networks with differences in compliance with the India’s national tobacco control law. The survey was administered to 108 respondents (n=51 and 57) in two districts, producing three distinct network maps about interaction, information-seeking and decision-making patterns within each district. The network measures of centrality, density, reciprocity, centralisation and E-I index were used to understand and compare across the two districts.ResultsMembers from the department of health, especially those in the District Tobacco Control Cell, were the most frequently consulted actors for information as they led district-level networks. The most common departments engaged beyond health were education, police and municipal. District 1’s network displayed high centralisation, with a district nodal officer who exercised a central role with the highest in-degree centrality. The district also exhibited greater density and reciprocity. District 2 showed a more dispersed pattern, where subdistrict health managers had higher betweenness centrality and acted as brokers in the network.ConclusionCollaboration and cooperation among sectors and departments are essential components of multisectoral policy. SNA provides a mechanism to uncover the nature of relationships and key actors in collaborative dynamics. It can be used as a visual learning tool for policy planners and implementers to understand the structure of actual implementation and concentrate their efforts to improve and enhance collaboration.

Equity impact of minimum unit pricing of alcohol on household health and finances among rich and poor drinkers in South Africa

IntroductionSouth Africa experiences significant levels of alcohol-related harm. Recent research suggests minimum unit pricing (MUP) for alcohol would be an effective policy, but high levels of income inequality raise concerns about equity impacts. This paper quantifies the equity impact of MUP on household health and finances in rich and poor drinkers in South Africa.MethodsWe draw from extended cost-effectiveness analysis (ECEA) methods and an epidemiological policy appraisal model of MUP for South Africa to simulate the equity impact of a ZAR 10 MUP over a 20-year time horizon. We estimate the impact across wealth quintiles on: (i) alcohol consumption and expenditures; (ii) mortality; (iii) government healthcare cost savings; (iv) reductions in cases of catastrophic health expenditures (CHE) and household savings linked to reduced health-related workplace absence.ResultsWe estimate MUP would reduce consumption more among the poorest than the richest drinkers. Expenditure would increase by ZAR 353 000 million (1 US$=13.2 ZAR), the poorest contributing 13% and the richest 28% of the increase, although this remains regressive compared with mean income. Of the 22 600 deaths averted, 56% accrue to the bottom two quintiles; government healthcare cost savings would be substantial (ZAR 3.9 billion). Cases of CHE averted would be 564 700, 46% among the poorest two quintiles. Indirect cost savings amount to ZAR 51.1 billion.ConclusionsA MUP policy in South Africa has the potential to reduce harm and health inequality. Fiscal policies for population health require structured policy appraisal, accounting for the totality of effects using mathematical models in association with ECEA methodology.

Guideline for feedback of individual genetic research findings for genomics research in Africa

As human genomics research in Africa continues to generate large amounts of data, ethical issues arise regarding how actionable genetic information is shared with research participants. The Human Heredity and Health in Africa Consortium (H3Africa) Ethics and Community Engagement Working group acknowledged the need for such guidance, identified key issues and principles relevant to genomics research in Africa and developed a practical guideline for consideration of feeding back individual genetic results of health importance in African research projects. This included a decision flowchart, providing a logical framework to assist in decision-making and planning for human genomics research projects. Although presented in the context of the H3Africa Consortium, we believe the principles described, and the decision flowchart presented here is applicable more broadly in African genomics research.