The social determinants of emerging infectious diseases in Africa

Houéto, David

doi:10.15406/mojph.2019.08.00286

Cited by 10 publications

(10 citation statements)

References 14 publications

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“…For Zika, low income populations living in the Recife favelas were much more likely to be exposed to the disease vector, reporting more mosquito biting relative to residents in other neighbourhoods -mainly due to poor sanitation with more than 90% of favela residents reliant on standing water -a prime location for mosquito breeding [10]. In terms of Ebola, reliance on bush meat consumption amongst the poorest communities may have increased exposure -as has increased encroachment into forests [11]. In terms of COVID-19, lower paid workers were much more likely to be exposed (e.g.…”

Section: Pathway 1: Unequal Exposurementioning

confidence: 99%

Pandemic inequalities: emerging infectious diseases and health equity

Bambra

2022

Int J Equity Health

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The frequency and scale of Emerging Infectious Diseases (EIDs) with pandemic potential has been increasing over the last two decades and, as COVID-19 has shown, such zoonotic spill-over events are an increasing threat to public health globally. There has been considerable research into EIDs – especially in the case of COVID-19. However, most of this has focused on disease emergence, symptom identification, chains of transmission, case prevalence and mortality as well as prevention and treatment. Much less attention has been paid to health equity concerns and the relationship between socio-economic inequalities and the spread, scale and resolution of EID pandemics. This commentary article therefore explores socio-economic inequalities in the nature of EID pandemics. Drawing on three diverse case studies (Zika, Ebola, COVID-19), it hypothesises the four main pathways linking inequality and infectious disease (unequal exposure, unequal transmission, unequal susceptibility, unequal treatment) – setting out a new model for understanding EIDs and health inequalities. It concludes by considering the research directions and policy actions needed to reduce inequalities in future EID outbreaks.

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Section: Pathway 1: Unequal Exposurementioning

confidence: 99%

Pandemic inequalities: emerging infectious diseases and health equity

Bambra

2022

Int J Equity Health

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“…These changes include increases in population size and density; urbanization; persistent poverty (especially in the expansion of urban slums); the number and movement of political, economic and environmental refugees; differences in infrastructure and science and technology; and poor health awareness [36]. The socio-economic environment contributes significantly to the health of individuals as well as communities [37] and is the root cause of health and health equity. These socio-economic drivers have contributed to the shifting global ecology of vector transmission that enabled COVID-19 to emerge worldwide, by dangerously uniting the human hosts, vectors and pathogen.…”

Section: Introductionmentioning

confidence: 99%

Influence of socio-ecological factors on COVID-19 risk: a cross-sectional study based on 178 countries/regions worldwide

Chen

et al. 2020

Preprint

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“…The methodologies included network analysis to examine topological dynamics of MERS-CoV (Yang and Jung, 2020), cross-section based descriptive analyses to explore the epidemiologic and clinical features of the diseases (Oboho et al, 2015), likelihood-based inference method to analyze cluster data for the reported MERS-CoV cases in South Korea (Kucharski and Althaus, 2015), systematic review of secondary data (Al-Tawfiq and Zemish, 2016;Park et al, 2018), framework analysis of epidemiological records (Cauchemeza et al, 2011), maximum likelihood estimation methods (Donnelly et al, 2003), Bayesian data augmentation framework (Cauchemez et al, 2011), etc. These studies revealed a diverse range of factors associated with the transmission of infectious diseases, including medical, healthcare, social, viral, host and environmental factors (Cauchemeza et al, 2011;Park et al, 2018;Al-Tawfiq and Zemish, 2016;Donnelly et al, 2003;Yeh et al, 2018;Hou eto 2019). Yeh et al (2018) further concluded that the risk factors for humans contracting infectious diseases include residence, occupation, location of leisure activity and density of transmitted vectors.…”

Section: Literature Reviewmentioning

confidence: 99%

A panel path analysis approach to the determinants of coronavirus disease 2019 transmission: does testing matter for confirmed cases?

Goswami

Ali

Islam

2020

JES

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PurposeThe main purpose of this study is to examine the role of the coronavirus disease 2019 (COVID-19) test on transmission data globally to reveal the fact that the actual picture of transmission history cannot be exposed if the countries do not perform the test adequately.Design/methodology/approachUsing Our World in Data for 212 countries and areas and 162 time periods daily from December 31, 2019, to June 09, 2020, on an unbalanced panel framework, we have developed a panel-based path analysis model to explore the interdependence of various actors of COVID-19 cases of transmission across the globe. After controlling for per capita gross domestic product (GDP), age structure and government stringency, we explore the proposition that COVID-19 tests affect transmission positively. As an anecdote, we also explore the direct, indirect and total effects of different potential determinants of transmission cases worldwide and gather an idea about each factor's relative role in a structural equation framework.FindingsUsing the panel path model, we find that a 1 standard deviation change in the number of tests results in a 0.70 standard deviation change in total cases per million after controlling for several variables like per capita GDP, government stringency and age population (above 65).Research limitations/implicationsIt is not possible to get balanced data of COVID-19 for all the countries for all the periods. Similarly, the socioeconomic, political and demographic variables used in the model are not observed daily, and they are only available on an annual basis.Practical implicationsCountries which cannot afford to carry out more tests are also the countries where transmission rates are suppressed downward and negatively manipulated.Social implicationsCross country collaboration in terms of COVID-19 test instruments, vaccination and technology transfer are urgently required. This collaboration may be sought as an alternative to foreign development assistance.Originality/valueThis article provides an alternative approach to modeling COVID-19 transmission through the panel path model where the test is considered as an endogenous determinant of transmission, and the endogeneity has been channeled through per capita GDP, government stringency and age structure without using any regression-based modeling like pooled ordinary least squares (OLS), fixed-effects, two-stage least squares or generalized method of moments (GMM). Endogeneity has been handled without using any instruments.

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The social determinants of emerging infectious diseases in Africa

Cited by 10 publications

References 14 publications

Pandemic inequalities: emerging infectious diseases and health equity

Pandemic inequalities: emerging infectious diseases and health equity

Influence of socio-ecological factors on COVID-19 risk: a cross-sectional study based on 178 countries/regions worldwide

A panel path analysis approach to the determinants of coronavirus disease 2019 transmission: does testing matter for confirmed cases?

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