Paul R Hunter1, Felipe J Colón-González2, Julii Brainard1, Batsirai Majuru1, Debora Pedrazzoli3, Ibrahim Abubakar4, Girmaye Dinsa5, Marc Suhrcke6, David Stuckler7, Tek-Ang Lim8, Jan C Semenza9. 1. Norwich Medical School. 2. School of Environmental Sciences, University of East Anglia, UK. 3. Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, UK. 4. Institute for Global Health, University College London, UK. 5. T.H. Chan School of Public Health, Harvard University, USA. 6. Centre for Health Economics, University of York, UK. 7. Dondena Research Centre, University of Bocconi, Italy. 8. Science and International Office, French Public Health Agency, France. 9. European Centre for Disease Prevention and Control (ECDC), Sweden.
Abstract
Aims: It is unclear how economic factors impact on the epidemiology of infectious disease. We evaluated the relationship between incidence of selected infectious diseases and economic factors, including economic downturn, in 13 European countries between 1970 and 2010. Methods: Data were obtained from national communicable disease surveillance centres. Negative binomial forms of the generalised additive model (GAM) and the generalised linear model were tested to see which best reflected transmission dynamics of: diphtheria, pertussis, measles, meningococcal disease, hepatitis B, gonorrhoea, syphilis, hepatitis A and salmonella. Economic indicators were gross domestic product per capita (GDPpc), unemployment rates and (economic) downturn. Results: GAM models produced the best goodness-of-fit results. The relationship between GDPpc and disease incidence was often non-linear. Strength and directions of association between population age, tertiary education levels, GDPpc and unemployment were disease dependent. Overdispersion for almost all diseases validated the assumption of a negative binomial relationship. Downturns were not independently linked to disease incidence. Conclusions: Social and economic factors can be correlated with many infections. However, the trend is not always in the same direction, and these associations are often non-linear. Economic downturn or recessions as indicators of increased disease risk may be better replaced by GDPpc or unemployment measures.
Aims: It is unclear how economic factors impact on the epidemiology of infectious disease. We evaluated the relationship between incidence of selected infectious diseases and economic factors, including economic downturn, in 13 European countries between 1970 and 2010. Methods: Data were obtained from national communicable disease surveillance centres. Negative binomial forms of the generalised additive model (GAM) and the generalised linear model were tested to see which best reflected transmission dynamics of: diphtheria, pertussis, measles, meningococcal disease, hepatitis B, gonorrhoea, syphilis, hepatitis A and salmonella. Economic indicators were gross domestic product per capita (GDPpc), unemployment rates and (economic) downturn. Results: GAM models produced the best goodness-of-fit results. The relationship between GDPpc and disease incidence was often non-linear. Strength and directions of association between population age, tertiary education levels, GDPpc and unemployment were disease dependent. Overdispersion for almost all diseases validated the assumption of a negative binomial relationship. Downturns were not independently linked to disease incidence. Conclusions: Social and economic factors can be correlated with many infections. However, the trend is not always in the same direction, and these associations are often non-linear. Economic downturn or recessions as indicators of increased disease risk may be better replaced by GDPpc or unemployment measures.
Authors: Colette Mair; Sema Nickbakhsh; Richard Reeve; Jim McMenamin; Arlene Reynolds; Rory N Gunson; Pablo R Murcia; Louise Matthews Journal: PLoS Comput Biol Date: 2019-12-13 Impact factor: 4.475
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