1921
Volume 100, Issue 2
  • ISSN: 0002-9637
  • E-ISSN: 1476-1645

Abstract

Abstract.

Matthew, a category 4 hurricane, struck Haiti on October 4, 2016, causing widespread flooding and damage to buildings and crops, and resulted in many deaths. The damage caused by Matthew raised concerns of increased cholera transmission particularly in Sud and Grand’Anse departments, regions which were hit most heavily by the storm. To evaluate the change in reported cholera cases following Hurricane Matthew on reported cholera cases, we used interrupted time series regression models of daily reported cholera cases, controlling for the impact of both rainfall, following a 4-week lag, and seasonality, from 2013 through 2016. Our results indicate a significant increase in reported cholera cases after Matthew, suggesting that the storm resulted in an immediate surge in suspect cases, and a decline in reported cholera cases in the 46-day post-storm period, after controlling for rainfall and seasonality. Regression models stratified by the department indicate that the impact of the hurricane was regional, with larger surges in the two most highly storm-affected departments: Sud and Grand’Anse. These models were able to provide input to the Ministry of Health in Haiti on the national and regional impact of Hurricane Matthew and, with further development, could provide the flexibility of use in other emergency situations. This article highlights the need for continued cholera prevention and control efforts, particularly in the wake of natural disasters such as hurricanes, and the continued need for intensive cholera surveillance nationally.

[open-access] This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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References

  1. Barzilay EJ, Schaad N, Magloire R, Mung KS, Boncy J, Dahourou GA, Mintz ED, Steenland MW, Vertefeuille JF, Tappero JW, , 2013. Cholera surveillance during the Haiti epidemic—the first 2 years. N Engl J Med 368: 599609. [Google Scholar]
  2. Ferreira S, , 2016. Cholera threatens Haiti after Hurricane Matthew. BMJ 355: i5516. [Google Scholar]
  3. Direction d'Épidémiologie de Laboratoire et de Récherches, 2016. Rapport du Réseau National de Surveillance. Sites Choléra, 52ème Semaine Épidémiologique 2016. Port-au-Prince, Haiti: Ministère de la Santé Publique et de la Population. [Google Scholar]
  4. Kirpich A, Weppelmann TA, Yang Y, Ali A, Morris JG, Jr. Longini IM, , 2015. Cholera transmission in ouest department of Haiti: dynamic modeling and the future of the epidemic. PLoS Negl Trop Dis 9: e0004153. [Google Scholar]
  5. Ali M, Nelson A, Lopez A, Sack D, , 2015. Updated global burden of cholera in endemic countries. PLoS Negl Trop Dis 9: e0003832. [Google Scholar]
  6. World Health Organization, 2010. Cholera vaccines: WHO position paper. Wkly Epidemiol Rec 85: 117128. [Google Scholar]
  7. Direction d'Épidémiologie de Laboratoire et de Recherches, 2016. Cholera Surveillance Data, 2013–2016. Port-au-Prince, Haiti: Ministère de la Santé Publique et de la Population. [Google Scholar]
  8. NOAA/NESDIS Center for Satelite Applications and Research, 2016. STAR Satellite Rainfall Estimates—Hydro-Estimator for Mexico, Central America, and the Caribbean. Washington, DC: U.S. Department of Commerce. [Google Scholar]
  9. R Core Team, 2016. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. [Google Scholar]
  10. Institut Haitien de Statistique et d'Informatique, 2015. Estimation de la Population 2015. Port-au-Prince, Haiti: Ministry of Economy and Finances. [Google Scholar]
  11. Hashizume M, Armstrong B, Hajat S, Wagatsuma Y, Faruque A, Hayashi T, Sack D, , 2008. The effect of rainfall on the incidence of cholera in Bangladesh. Epidemiology 19: 103110. [Google Scholar]
  12. Milojavec A, Armstrong B, Hashizume M, McAllister K, Faruque A, Yunus M, Streatfield P, Moji K, Wilkinson P, , 2012. Health effects of flooding in rural Bangladesh. Epidemiology 23: 107115. [Google Scholar]
  13. Lopez Bernal J, Cummins S, Gasparrini A, , 2016. Interrupted time series regression for the evaluation of public health interventions: a tutorial. Int J Epidemiol 0: 18. [Google Scholar]
  14. Gasparrini A, Gorini G, Barchielli A, , 2009. On the relationship between smoking bans and incidence of acute myocardial infarction. Eur J Epidemiol 24: 597602. [Google Scholar]
  15. Bhaskaran K, Gasparrini A, Hajat S, Smeeth L, Armstrong B, , 2013. Time series regression studies in environmental epidemiology. Int J Epidemiol 42: 11871195. [Google Scholar]
  16. Barone-Adesi F, Gasparrini A, Vizzini L, Merlettie F, Richiardi L, , 2011. Effects of Italian smoking regulation on rates of hospital admission for acute coronary events: a country-wide study. PLoS One : e17419. [Google Scholar]
  17. Alam MT, Weppelmann TA, Longini IM, De Rochars V, Morris J, Ali A, , 2015. Increased isolation frequency of toxigenic Vibrio cholerae O1 from environmental monitoring sites in Haiti. PLoS One 10: e0124098. [Google Scholar]
  18. Huq A, 2005. Critical factors influencing the occurrence of Vibrio cholerae in the environment of Bangladesh. Appl Environ Microbiol 71: 46454654. [Google Scholar]
  19. Hashizume M, Faruque A, Wagatsuma Y, Hayashi T, Armstrong B, , 2010. Cholera in Bangladesh: climatic components of seasonal variation. Epidemiology 21: 706710. [Google Scholar]
  20. Eisenberg MC, Kujbida G, Tuite AR, Fisman DN, Tien JH, , 2013. Examining rainfall and cholera dynamics in Haiti using statistical and dynamic modeling approaches. Epidemics 5: 197207. [Google Scholar]
  21. Mendelsohn J, Dawson T, , 2006. Climate and cholera in KwaZulu-Natal, South Africa: the role of environmental factors and implications for epidemic preparedness. Int J Hyg Environ Health 211: 156162. [Google Scholar]
  22. Partners in Health, 2017. Hôpital Universitaire de Mirebalais. Available at: http://www.pih.org/pages/mirebalais. Accessed 2017.
  23. Rebaudet S, Gazin P, Barrais R, Moore S, Rossignol E, Barthelemy N, Gaudart J, Boncy J, Magloire R, Piarroux R, , 2013. The dry season in Haiti: a window of opportunity to eliminate cholera. PLoS Curr 5: pii 2193a0ec4401d9526203af12e5024dd. [Google Scholar]
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  • Received : 08 Dec 2017
  • Accepted : 30 Sep 2018
  • Published online : 26 Dec 2018

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