TY - JOUR
T1 - Spatio-temporal dynamics of measles outbreaks in Cameroon
AU - Parpia, Alyssa S.
AU - Skrip, Laura A.
AU - Nsoesie, Elaine O.
AU - Ngwa, Moise C.
AU - Abah Abah, Aristide S.
AU - Galvani, Alison P.
AU - Ndeffo-Mbah, Martial L.
N1 - Funding Information:
The authors would like to acknowledge the provision of data from the Cameroon Ministry of Health and three anonymous reviewers for very constructive comments. This study was funded by the Overlook International Foundation, the National Institutes of Health and faculty startup funding from Texas A&M College of Veterinary Medicine and Biomedical Sciences. A.S.P is supported by the Yale Climate Change and Health Initiative through a grant from the Overlook International Foundation. M.LN.M. is supported by faculty startup funding from Texas A&M. A.P.G. is supported by NIH, United States grant U01 GM087719. E.O.N. is supported by NIH grant K01ES025438-04. Authors' contributions: A.S.P. and M.L.N.M. designed the study; A.S.A.A. acquired the data; A.S.P. performed the analysis; A.S.P. E.O.N. and M.L.N.M. interpreted the data. M.C.N. contributed the health district–level shapefile. A.S.P. L.S. A.P.G. and M.L.N.M. drafted the manuscript. All authors read and provided edits on the final paper.
Funding Information:
This study was funded by the Overlook International Foundation, the National Institutes of Health and faculty startup funding from Texas A&M College of Veterinary Medicine and Biomedical Sciences . A.S.P is supported by the Yale Climate Change and Health Initiative through a grant from the Overlook International Foundation. M.LN.M. is supported by faculty startup funding from Texas A&M . A.P.G. is supported by NIH, United States grant U01 GM087719 . E.O.N. is supported by NIH grant K01ES025438-04.
Publisher Copyright:
© 2019 Elsevier Inc.
PY - 2020/2
Y1 - 2020/2
N2 - Purpose: In 2012, Cameroon experienced a large measles outbreak of over 14,000 cases. To determine the spatio-temporal dynamics of measles transmission in Cameroon, we analyzed weekly case data collected by the Ministry of Health. Methods: We compared several multivariate time-series models of population movement to characterize the spatial spread of measles in Cameroon. Using the best model, we evaluated the contribution of population mobility to disease transmission at increasing geographic resolutions: region, department, and health district. Results: Our spatio-temporal analysis showed that the power law model, which accounts for long-distance population movement, best represents the spatial spread of measles in Cameroon. Population movement between health districts within departments contributed to 7.6% (range: 0.4%–13.4%) of cases at the district level, whereas movement between departments within regions contributed to 16.0% (range: 1.3%–23.2%) of cases. Long-distance movement between regions contributed to 16.7% (range: 0.1%–59.0%) of cases at the region level, 20.1% (range: 7.1%–30.0%) at the department level, and 29.7% (range: 15.3%–47.6%) at the health district level. Conclusions: Population long-distance mobility is an important driver of measles dynamics in Cameroon. These findings demonstrate the need to improve our understanding of the roles of population mobility and local heterogeneity of vaccination coverage in the spread and control of measles in Cameroon.
AB - Purpose: In 2012, Cameroon experienced a large measles outbreak of over 14,000 cases. To determine the spatio-temporal dynamics of measles transmission in Cameroon, we analyzed weekly case data collected by the Ministry of Health. Methods: We compared several multivariate time-series models of population movement to characterize the spatial spread of measles in Cameroon. Using the best model, we evaluated the contribution of population mobility to disease transmission at increasing geographic resolutions: region, department, and health district. Results: Our spatio-temporal analysis showed that the power law model, which accounts for long-distance population movement, best represents the spatial spread of measles in Cameroon. Population movement between health districts within departments contributed to 7.6% (range: 0.4%–13.4%) of cases at the district level, whereas movement between departments within regions contributed to 16.0% (range: 1.3%–23.2%) of cases. Long-distance movement between regions contributed to 16.7% (range: 0.1%–59.0%) of cases at the region level, 20.1% (range: 7.1%–30.0%) at the department level, and 29.7% (range: 15.3%–47.6%) at the health district level. Conclusions: Population long-distance mobility is an important driver of measles dynamics in Cameroon. These findings demonstrate the need to improve our understanding of the roles of population mobility and local heterogeneity of vaccination coverage in the spread and control of measles in Cameroon.
KW - Cameroon
KW - Measles outbreaks
KW - Multivariate models
KW - Spatio-temporal analysis
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U2 - 10.1016/j.annepidem.2019.10.007
DO - 10.1016/j.annepidem.2019.10.007
M3 - Article
C2 - 31902625
AN - SCOPUS:85077256556
VL - 42
SP - 64-72.e3
JO - Annals of Epidemiology
JF - Annals of Epidemiology
SN - 1047-2797
ER -