Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 May 4;2(2):203-217.
doi: 10.1016/j.idm.2017.03.003. eCollection 2017 May.

Climate variability and infectious diseases nexus: Evidence from Sweden

Franklin Amuakwa-Mensah  1 , George Marbuah  1 , Mwenya Mubanga  2
Affiliations

Climate variability and infectious diseases nexus: Evidence from Sweden

Franklin Amuakwa-Mensah et al. Infect Dis Model. .

Abstract

Many studies on the link between climate variability and infectious diseases are based on biophysical experiments, do not account for socio-economic factors and with little focus on developed countries. This study examines the effect of climate variability and socio-economic variables on infectious diseases using data from all 21 Swedish counties. Employing static and dynamic modelling frameworks, we observe that temperature has a linear negative effect on the number of patients. The relationship between winter temperature and the number of patients is non-linear and "U" shaped in the static model. Conversely, a positive effect of precipitation on the number of patients is found, with modest heterogeneity in the effect of climate variables on the number of patients across disease classifications observed. The effect of education and number of health personnel explain the number of patients in a similar direction (negative), while population density and immigration drive up reported cases. Income explains this phenomenon non-linearly. In the dynamic setting, we found significant persistence in the number of infectious and parasitic-diseased patients, with temperature and income observed as the only significant drivers.

Keywords: Climate variability; Infectious diseases; Sweden.

PubMed Disclaimer

Figures

Fig. 1
Fig. 1
Distribution of patients across various infectious and parasitic disease (1998–2014). Note: A00-A09 Intestinal infectious diseases; A15-A19 Tuberculosis; A20-A28 Certain zoonotic bacterial diseases; A30-A49 Other bacterial diseases; A50-A64 Infections with a predominantly sexual mode of transmission; A65-A69 Other spirochaetal diseases; A70-A74 Other diseases caused by chlamydiae; A75-A79 Rickettsioses; A80-A89 Viral infections of the central nervous system; A90-A99; Arthropod-borne viral fevers and viral haemorrhagic fevers; B00-B09 Viral infections characterized by skin and mucous membrane lesions; B15-B19 Viral hepatitis; B20-B24 Human immunodeficiency virus [HIV] disease; B25-B34 Other viral diseases; B35-B49 Mycoses; B50-B64 Protozoal diseases; B65-B83 Helminthiases; B85-B89 Pediculosis, acariasis and other infestations; B90-B94 Sequelae of infectious and parasitic diseases; B95-B98 Bacterial, viral and other infectious agents; B99-B99 Other infectious diseases.
Fig. 2
Fig. 2
Distribution of infectious and parasitic disease patients across counties (1998–2014).
See this image and copyright information in PMC

References

    1. Al A.D. Epidemiology and ecology of Tularemia in Sweden, 1984–2012. Emerging Infectious Disease Journal - CDC. 2015;21(1) January 2015. - PMC - PubMed
    1. Amuakwa-Mensah F., Marbuah G., Mubanga M. 2016. Climate variability and infectious diseases nexus: Evidence from Sweden. FAERE-Fr, Association of Environmental and Resource Working Paper, 2016.02. - PMC - PubMed
    1. Andersson T., Ahlbom A., Carlsson S. Diabetes prevalence in Sweden at present and projections for year 2050. PLOS ONE. 2015;10:e0143084. - PMC - PubMed
    1. Anell A., Glenngard A.H., Merkur S. Sweden: Health system review. Health Systems in Transition. 2012;14:1–159. - PubMed
    1. Arellano M., Bond S. Some tests of specification for panel Data: Monte carlo evidence and an application to employment equations. Review of Economic Studies. 1991;58:277–297.

LinkOut - more resources