Near real-time forecasting for cholera decision making in Haiti after Hurricane Matthew

PLoS Computational Biology

Volumn 14, Issue 5, 2018, Pages

  Pasetto, Damiano ^a   Finger, Flavio ^a,b   Camacho, Anton ^b,c   Grandesso, Francesco ^c   Cohuet, Sandra ^c   Lemaitre, Joseph C ^a   Azman, Andrew S ^d   Luquero, Francisco J ^c,d   Bertuzzo, Enrico ^e   Rinaldo, Andrea ^a,f  

^a EPFL   (Switzerland)

^b LONDON SCHOOL OF HYGIENE AND TROPICAL MEDICINE   (United Kingdom)

^c EPICENTRE   (France)

^d JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH   (United States)

^e CA' FOSCARI UNIVERSITY OF VENICE   (Italy)

^f UNIVERSITY OF PADOVA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

DISEASES; RAIN; RISK ASSESSMENT; RISK MANAGEMENT; RISK PERCEPTION; VACCINES; WEATHER FORECASTING;

COMMUNITY MODEL; COMPUTATIONAL MODELLING; DECISIONS MAKINGS; FIELD RESEARCH; HEALTHCARE RESOURCES; META COMMUNITIES; NEAR-REAL TIME; PREDICTION INTERVAL; REAL-TIME FORECASTING; SPATIALLY EXPLICIT;

HURRICANES;

CHOLERA VACCINE; RAIN;

ARTICLE; BACTERIAL TRANSMISSION; CHOLERA; DECISION MAKING; EPIDEMIC; FIELD EXPERIMENT; FORECASTING; HAITI; HUMAN; HURRICANE; INCIDENCE; MATHEMATICAL MODEL; PREDICTION; QUANTITATIVE ANALYSIS; RISK ASSESSMENT; SPATIAL ANALYSIS; VACCINATION; COMPUTER SIMULATION; STATISTICS AND NUMERICAL DATA; TRANSMISSION;

CHOLERA; COMPUTER SIMULATION; CYCLONIC STORMS; DECISION MAKING; DISEASE OUTBREAKS; FORECASTING; HAITI; HUMANS; INCIDENCE;

EID: 85048164935     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1006127     Document Type: Article

References (50)

1. Khan R, Anwar R, Akanda S, McDonald MD, Huq A, Jutla A, et al. Assessment of Risk of Cholera in Haiti following Hurricane Matthew. The American Journal of Tropical Medicine and Hygiene. 2017;97(3):896–903. doi: 10.4269/ajtmh.17-0048 28749774
2. Gaudart J, Rebaudet S, Barrais R, Boncy J, Faucher B, Piarroux M, et al. Spatio-temporal dynamics of cholera during the first year of the epidemic in Haiti. PLoS Neglected Tropical Diseases. 2013;7(4):e2145. doi: 10.1371/journal.pntd.0002145 23593516
3. Rinaldo A, Bertuzzo E, Mari L, Righetto L, Blokesch M, Gatto M, et al. Reassessment of the 2010-2011 Haiti cholera outbreak and rainfall-driven multiseason projections. Proceedings of the National Academy of Sciences of the United States of America. 2012;109(17):6602–6607. doi: 10.1073/pnas.1203333109 22505737
4. Eisenberg MC, Kujbida G, Tuite AR, Fisman DN, Tien JH, Examining rainfall and cholera dynamics in Haiti using statistical and dynamic modeling approaches. Epidemics. 2013;5(4):197–207. doi: 10.1016/j.epidem.2013.09.004 24267876
5. UN Office for the Coordination of Humanitarian Affairs. Haiti: Hurricane Matthew Humanitarian Dashboard; 2017 (accessed on 2017-09-03). Available from: http://reliefweb.int/report/haiti/haiti-hurricane-matthew-humanitarian-dashboard-february-2017.
6. UNICEF. Haiti WASH Sector Situation Report#1; 2016 (accessed on 2017-11-10). Available from: https://www.unicef.org/appeals/files/UNICEF_Haiti_Hurricane_Matthew_WASH_Sector_Sitrep_29_Oct_2016.pdf.
7. Bertuzzo E, Azaele S, Maritan A, Gatto M, Rodriguez-Iturbe I, Rinaldo A, On the space-time evolution of a cholera epidemic. Water Resources Research. 2008;44:W01424. doi: 10.1029/2007WR006211
8. Bertuzzo E, Mari L, Righetto L, Gatto M, Casagrandi R, Rodriguez-Iturbe I, et al. Prediction of the spatial evolution and effects of control measures for the unfolding Haiti cholera outbreak. Geophysical Research Letters. 2011;38:L06403. doi: 10.1029/2011GL046823
9. Mari L, Bertuzzo E, Righetto L, Casagrandi R, Gatto M, Rodriguez-Iturbe I, et al. Modelling cholera epidemics: the role of waterways, human mobility and sanitation. Journal of the Royal Society Interface. 2012;9:376–388. doi: 10.1098/rsif.2011.0304
10. Mari L, Bertuzzo E, Righetto L, Casagrandi R, Gatto M, Rodriguez-Iturbe I, et al. On the role of human mobility in the spread of cholera epidemics: towards an epidemiological movement ecology. Ecohydrology. 2012;5:531–540. doi: 10.1002/eco.262
11. Mari L, Bertuzzo E, Finger F, Casagrandi R, Gatto M, Rinaldo A, On the predictive ability of mechanistic models for the Haitian cholera epidemic. Journal of the Royal Society Interface. 2015;12(104):20140840. doi: 10.1098/rsif.2014.0840
12. Azman AS, Parker LA, Rumunu J, Tadesse F, G F, et al. Effectiveness of one dose of oral cholera vaccine in response to an outbreak: a case-cohort study. The Lancet Global Health. 2016;4(11):e856–e863. doi: 10.1016/S2214-109X(16)30211-X 27765293
13. Finger F, Genolet T, Mari L, de Magny GC, Manga NM, Rinaldo A, Bertuzzo E, Mobile phone data highlights the role of mass gatherings in the spreading of cholera outbreaks. Proceedings of the National Academy of Science of the United States of America. 2016;113(23):6421–6426. doi: 10.1073/pnas.1522305113
14. Pasetto D, Finger F, Rinaldo A, Bertuzzo E, Real-time projections of cholera outbreaks through data assimilation and rainfall forecasting. Advances in Water Resources. 2017;108:345–356. doi: 10.1016/j.advwatres.2016.10.004
15. Rinaldo A, Bertuzzo E, Mari L, Blokesch M, Gatto M, Modeling key drivers of cholera transmission dynamics provides new perspectives for parasitology. Trends in Parasitology. 2017;33(8):587–599. doi: 10.1016/j.pt.2017.04.002 28483382
16. Vital M, Fuchslin HP, Hammes F, Egli T, Growth of Vibrio cholerae O1 Ogawa Eltor in freshwater. Microbiology. 2007;153(7):1993–2001. doi: 10.1099/mic.0.2006/005173-0 17600045
17. Ruiz-Moreno D, Pascual M, Bouma M, Dobson A, Cash B, Cholera seasonality in Madras (1901–1940): dual role for rainfall in endemic and epidemic regions. EcoHealth. 2007;4(1):52–62. doi: 10.1007/s10393-006-0079-8
18. Hashizume M, Armstrong B, Hajat S, Wagatsuma Y, Faruque AS, Hayashi T, Sack DA, The effect of rainfall on the incidence of cholera in Bangladesh. Epidemiology. 2008;19(55):103–110. doi: 10.1097/EDE.0b013e31815c09ea 18091420
19. Emch M, Feldacker C, Islam MS, Ali M, Seasonality of cholera from 1974 to 2005: a review of global patterns. International Journal of Health Geographics. 2008;7(31). doi: 10.1186/1476-072X-7-31 18570659
20. de Magny CG, Thiaw W, Kumar V, Manga NM, Diop BM, et al. Cholera Outbreak in Senegal in 2005: Was Climate a Factor?PLOS ONE. 2012;7(8):e44577. doi: 10.1371/journal.pone.0044577 22952995
21. Boelee E., Yohannes M., Poda JN, et al. Options for water storage and rainwater harvesting to improve health and resilience against climate change in Africa. Regional Environmental Change. 2013;13:509–519. doi: 10.1007/s10113-012-0287-4
22. Lipp EK, Huq A, Colwell RR, Effects of global climate on infectious disease: the cholera model. Clinical Microbiology Reviews. 2002;15(4):757–770. doi: 10.1128/CMR.15.4.757-770.2002 12364378
23. Rebaudet S, Sudre B, Faucher B, Piarroux R, Environmental determinants of cholera outbreaks in inland Africa: a systematic review of main transmission foci and propagation routes. The Journal of Infectious Diseases. 2013;208Suppl 1:s46–54. doi: 10.1093/infdis/jit195 24101645
24. Rebaudet S, Sudre B, Faucher B, Piarroux R, Cholera in coastal Africa: a systematic review of its heterogeneous environmental determinants. The Journal of Infectious Diseases. 2013;208Suppl 1:S98–106. doi: 10.1093/infdis/jit202 24101653
25. Jutla A, Whitcombe E, Hasan N, Haley B, Akanda A, Huq A, Alam M, Sack RB, Colwell R, Environmental factors influencing epidemic cholera. The American Journal of Tropical Medicine and Hygiene. 2013;89(3), 597–607. doi: 10.4269/ajtmh.12-0721 23897993
26. Bertuzzo E, Finger F, Mari L, Gatto M, Rinaldo A, On the probability of extinction of the Haiti cholera epidemic. Stochastic Environmental Research and Risk Assessment. 2016;30:2043–2055. doi: 10.1007/s00477-014-0906-3
27. Camacho A, Pasetto D, Finger F, Bertuzzo E, Cohuet S, Grandesso F, et al. Prediction of cholera dynamics in Haiti following the passage of Hurricane Matthew. Paris, France: Epicentre; 2016. Available from: https://epicentre-msf.shinyapps.io/haiti-2016-cholera/Epicentre-EPFL-modelling-cholera-haiti_20161111.pdf.
28. Camacho A, Pasetto D, Finger F, Bertuzzo E, Cohuet S, Grandesso F, et al. Benefit of vaccination in protecting the departments of Grand’Anse, Ouest and Sud against a potential second epidemic wave of cholera. Paris, France: Epicentre; 2016. Available from: https://epicentre-msf.shinyapps.io/haiti-2016-cholera/_w_e2c22dbe/Epicentre-EPFL-modelling-cholera-haiti_20161223.pdf.
29. ERCC ECHO. Haiti—Hurricane Matthew—Damage assessment and ECHO Response, Emergency Response Coordination Centre (ERCC), European Commission, Humanitarian Aid and Civil Protection; 2016 (accessed on 2017-14-04). Available from: http://erccportal.jrc.ec.europa.eu/getdailymap/docId/1774.
30. PAHO W. Distribution of suspected cholera cases in Haiti by epidemiological week; 2016. Available from: ihttp://ais.paho.org/phip/viz/ed_haiticoleracases.asp.
31. Pezzoli L, Deployments from the oral cholera vaccine stockpile, 2013–2017. Weekly epidemiological record. 2017; 92(32):437–42. World Health Organization, Geneva.
32. Huffman GJ, Bolvin DT, Braithwaite D, Hsu K, Joyce R, Kidd C, et al. Integrated Multi-satellitE Retrievals for GPM (IMERG). NASA’s Precipitation Processing Center; 2015 (accessed on 2017-10-17). Available from: https://pmm.nasa.gov/sites/default/files/document_files/IMERG_ATBD_V4.5.pdf.
33. Abubakar A, Azman AS, Rumunu J, Ciglenecki I, Helderman T, West H, et al. The first use of the global oral cholera vaccine emergency stockpile: lessons from South Sudan. PLoS Medicine. 2015;12(11):e1001901doi: 10.1371/journal.pmed.1001901 26576044
34. Ferreras E, Chizema-Kawesha E, Blake A, Chewe O, Mwaba J, Zulu G, et al. Single-dose cholera vaccine in response to an outbreak in Zambia. New England Journal of Medicine. 2018;378(6):577–579. doi: 10.1056/NEJMc1711583 29414267
35. International Medical Corps: Hurricane Matthew Situation Report #7 December 13, 2016 (accessed on 2018-03-01) Available from: https://reliefweb.int/report/haiti/international-medical-corps-hurricane-matthew-situation-report-7-december-13-2016.
36. Bertuzzo E, Casagrandi R, Gatto M, Rodriguez-Iturbe I, Rinaldo A, On spatially explicit models of cholera epidemics. Journal of the Royal Society Interface. 2010;7:321–333. doi: 10.1098/rsif.2009.0204
37. Qadri F, Wierzba TF, Ali M, Chowdhury F, Khan AI, Saha A, et al. Efficacy of a single-dose, inactivated oral cholera vaccine in Bangladesh. New England Journal of Medicine. 2016;374(18):1723–1732. doi: 10.1056/NEJMoa1510330 27144848
38. Tohme RA, François J, Wannemuehler K, Iyengar P, Dismer A, Adrien P, et al. Oral cholera vaccine coverage, barriers to vaccination, and adverse events following vaccination, Haiti, 2013. Emerging Infectious Diseases. 2015;21(6):984–991. doi: 10.3201/eid2106.141797 25988350
39. Bengtsson L, Gaudart J, Lu X, Moore S, Wetter E, Sallah K, et al. Using mobile phone data to predict the spatial spread of cholera. Scientific Reports. 2015;5:89–93. doi: 10.1038/srep08923
40. Global Task Force on Cholera Control. Ending cholera—A global roadmap to 2030. WHO; 2017. Available from: http://www.who.int/cholera/publications/global-roadmap.pdf?ua=1.
41. Zaidi A, Make plans to eliminate cholera outbreaks. Nature. 2017;550:9. doi: 10.1038/550009a 28980651
42. Codeço C, Endemic and epidemic dynamics of cholera: the role of the aquatic reservoir. BMC Infectious Diseases. 2001;1(1). doi: 10.1186/1471-2334-1-1 11208258
43. Erlander S, Stewart NF, The Gravity Model in Transportation Analysis—Theory and Extensions. Zeist, The Netherlands: VSP Books; 1990.
44. Righetto L, Bertuzzo E, Mari L, Schild E, Casagrandi R, Gatto M, et al. Rainfall mediations in the spreading of epidemic cholera. Advances in Water Resources. 2013;60:34–46. doi: 10.1016/j.advwatres.2013.07.006
45. Piarroux R, Barrais R, Faucher B, Haus R, Piarroux M, Gaudart J, et al. Understanding the cholera epidemic, Haiti. Emerging Infectious Diseases. 2011;17:1161–1168. doi: 10.3201/eid1707.110059 21762567
46. Shaman J, Yang W, Kandula S, Inference and forecast of the current West African Ebola outbreak in Guinea, Sierra Leone and Liberia. PLoS Currents Outbreaks. 2014;6.
47. D’Silva JP, Eisenberg MC, Modeling spatial invasion of Ebola in West Africa. Journal of Theoretical Biology. 2017;428(Supplement C):65–75. doi: 10.1016/j.jtbi.2017.05.034 28551366
48. Shaman J, Karspeck A, Forecasting seasonal outbreaks of influenza. Proceedings of the National Academy of Sciences of the United States of America. 2012;109(50):20425–20430. doi: 10.1073/pnas.1208772109 23184969
49. Evensen G, The Ensemble Kalman Filter: theoretical formulation and practical implementation. Ocean Dyn. 2003;53(4):343–367. doi: 10.1007/s10236-003-0036-9
50. Livings DM, Dance SL, Nichols NK, Unbiased ensemble square root filters. Physica D: Nonlinear Phenomena. 2008;237(8):1021–1028. doi: 10.1016/j.physd.2008.01.005