The Syndemic and One Health Nature of Pandemics

The interdependence of humans, animals, plants, and their social and abiotic environment is highlighted by past and recent pandemics. A good example to understand and tackle threats to ecosystems is the COVID-19 pandemic. A syndemic is a complex and multilevel phenomenon of epidemics interacting synergistically at individual, societal, and environmental levels. Understanding the syndemic nature of pandemics will facilitate the adoption of a One Health approach to improve planetary health. To address the eco-complexity underlying One Health issues, the development of intelligence management systems through a planetary perspective is of key importance. This requires the capacity to capture, process, and communicate data on human, animal, and plant health and well-being, and on their social and environmental determinants. The implementation of such systems will need political commitment at all levels of action, deployment of adequate resources and expertise, reliable and comprehensive data flowing pathways through interoperable, flexible, and secure data sharing systems.

What are the Environmental Determinants to Participate Among Stroke Survivors in Africa? a Scoping Review

Background Stroke is the main cause of serious long-term disability worldwide, and it is the second commonest cause of death and a leading cause of adult disability. Two-thirds of stroke cases occur in low- and middle-income countries, which all African countries fall. In Africa, the incidence and survival rate of stroke is increasing. Various personal and environmental factors limit the participation of stroke survivors. As a result, in this review, we aimed to review the environmental factors that are influencing the participation of stroke survivors in Africa. Methods Five electronic databases were systematically searched in August 2021 and identified articles were screened by three authors based on predetermined criteria. We followed Arksey and O'Malley (2005) framework and the whole finding is reported using PRISMA-ScR. No date restrictions were imposed, and we included any type of papers including grey literature. Results 584 articles were generated by our search, after removing duplicates, the title and abstract of 497 articles were screened. From the screening, 42 articles were selected for full article review from which 12 met the criteria to be included. We also manually searched and included one more article for the review. Conclusion Studies were mainly conducted in South Africa and assessed the adult population. We followed the International Classification of Functioning, Disability and Health (ICF) framework for the environmental determinants to present our findings. Products and Technology; Natural Environment and Human-Made Changes to Environment; and Services, Systems and Policies found to be a barrier for participation. Conversely, stroke survivors are getting good support from their immediate family and health professionals, which is found to be facilitating. This review could be used by policymakers to understand the environmental barriers that are hindering participation and help to improve the accessibility of the environment so stroke survivors can participate in the community.

Socioeconomic determinants of teenage pregnancy and early motherhood in the United Kingdom: A perspective

The United Kingdom has one of the highest teenage birth rates among countries in western Europe. Government initiatives such as the Teenage Pregnancy Strategy introduced by the labor government in 1999 to reduce the teenage pregnancy rate by half in ten years could be responsible for the steady decline in teenage conception and childbirth for the past two decades. However, to sustain this decrease it is crucial to consider the broader socioeconomic and environmental determinants of teenage pregnancy at the population level. A selected literature search was conducted in this respect to highlight the factors that could be neglected by recent interventions on teenage pregnancy and childbirth in the United Kingdom.

Determinants of health

The determinants of health are the biological, psychological, behavioural, social, economic, and environmental factors that determine the health of individuals and populations. Socially or politically conditioned inequalities in the distribution of determinants lead to inequities in health within or between countries. The ways that determinants act on health are complex, involving interactions between factors and effects occurring over differing timespans. These complexities present challenges for research and public policy, to understand and take action on determinants, to improve population health, and/or to reduce health inequities. In this chapter we review the four main categories of biological, behavioural, social, and environmental determinants. We then discuss the topic of social determinants of health in more detail and review a number of the main factors identified in contemporary public health literature; from education, employment, and gender to determinants of Indigenous health, and commercial determinants of health. In a later section of the chapter (‘The complexity of determinants and their interactions’) we look at some of the challenges raised by the complex, multifactorial nature of determinants of health for research, health practice, and policy action. In the final section, we discuss two particular political challenges facing governments and international bodies seeking to take action on determinants of health and health equity.

Zika virus infection and microcephaly: spatial analysis and socio-environmental determinants in a region of high Aedes aegypti infestation in the Central-West Region of Brazil

Background More than 5 years after the Zika virus (ZIKV) epidemic, Zika infection remains a major concern in regions with high Aedes infestation. The objectives of this study were (i) to identify clusters of ZIKV infection and microcephaly, and/or central nervous system (CNS) alterations associated with congenital infection during the epidemic peak in 2016 and subsequently, in 2017 and 2018; (ii) to measure the non-spatial correlation between ZIKV infection and microcephaly and/or CNS alterations associated with congenital infection; and (iii) to analyse the sociodemographic/economic, health, and environmental determinants associated with the incidence of ZIKV in a region of high infestation by Aedes aegypti in the Central-West Region of Brazil. Methods This ecological study analysed 246 municipalities in the state of Goiás (6.9 million inhabitants). The data were obtained from the Information System for Notifiable Diseases (ZIKV cases) and the Public Health Event Registry (microcephaly and/or CNS alterations associated with congenital infection). Incidence rates and prevalence of ZIKA infection were smoothed by an empirical Bayesian estimator (LEbayes), producing the local empirical Bayesian rate (LEBR). In the spatial analysis, ZIKV infection and microcephaly cases were georeferenced by the municipality of residence for 2016 and grouped for 2017 and 2018. Global Moran's I and the Hot Spot Analysis tool (Getis-Ord Gi* statistics) were used to analyse the spatial autocorrelation and clusters of ZIKV infection and microcephaly, respectively. A generalised linear model from the Poisson family was used to assess the association between ecological determinants and the smoothing incidence rate of ZIKV infection. Results A total of 9892 cases of acute ZIKV infection and 121 cases of microcephaly were confirmed. The mean LEBR of the ZIKV infection in the 246 municipalities was 22.3 cases/100,000 inhabitants in 2016, and 10.3 cases/100,000 inhabitants in 2017 and 2018. The LEBR of the prevalence rate of microcephaly and/or CNS alterations associated with congenital infection was 7 cases/10,000 live births in 2016 and 2 cases/10,000 live births during 2017–2018. Hotspots of ZIKV infection and microcephaly cases were identified in the capital and neighbouring municipalities in 2016, with new clusters in the following years. In a multiple regression Poisson analysis, ZIKV infection was associated with higher population density, the incidence of dengue, Aedes larvae infestation index, and average rainfall. The important determinant of ZIKV infection incidence reduction was the increase in households attended by endemic disease control agents. Conclusions Our analyses were able to capture, in a more granular way, aspects that make it possible to inform public managers of the sentinel areas identified in the post-epidemic hotspots.