| Literature DB >> 26234531 |
Mark O Nanyingi1,2,3, Peninah Munyua4, Stephen G Kiama5, Gerald M Muchemi2, Samuel M Thumbi6,7, Austine O Bitek8,9, Bernard Bett10, Reese M Muriithi9, M Kariuki Njenga6,7.
Abstract
BACKGROUND: Rift Valley Fever (RVF) is a mosquito-borne viral zoonosis that was first isolated and characterized in 1931 in Kenya. RVF outbreaks have resulted in significant losses through human illness and deaths, high livestock abortions and deaths. This report provides an overview on epidemiology of RVF including ecology, molecular diversity spatiotemporal analysis, and predictive risk modeling.Entities:
Keywords: Rift Valley Fever; epidemiology; modeling; spatiotemporal
Year: 2015 PMID: 26234531 PMCID: PMC4522434 DOI: 10.3402/iee.v5.28024
Source DB: PubMed Journal: Infect Ecol Epidemiol ISSN: 2000-8686
Fig. 1PRISMA flow chart diagram describing the studies selection process for inclusion in this review [adapted and modified from (19)].
Fig. 2Map of Africa and Arabian Peninsula illustrating the spatial and temporal distribution of Rift Valley status from the first suspected case in 1912. Total number of human deaths (HD) is indicated for selected countries for all outbreak periods. Based on (2, 5–7, 10–12, 14, 16, 22, 23, 25, 40, 46, 54, 75, 80).
Fig. 3Map of Africa and the Arabian Peninsula illustrating the spatial and temporal distribution of Rift Valley cumulative outbreaks in days from 1977 to 2012 (2, 5–7, 10–12, 22, 23, 25, 40, 46, 80).
Characteristics of the eligible studies investigating RVF epidemiology, ecology, risk factors, and spatial modeling 1931–2012
| Morbidity and mortality estimates | |||||||||
|---|---|---|---|---|---|---|---|---|---|
|
| |||||||||
| Animals | Humans | ||||||||
| Year(s) | Geographic distribution | Study design | Research questions/objectives | Reported cases | Deaths | Reported cases | Deaths | Estimated impact in US$ (×106) | References |
| 1931 | Kenya | Cross-sectional | Risk factors and ecology | nd | 4,700 | nd | nd | nd | ( |
| 1950–1951 | South Africa | Cross-sectional | Epidemiology and spatial modeling | 600,000 | 100,000 | nd | nd | nd | ( |
| 1977–1978 | Egypt | Cross-sectional | Epidemiology and socioeconomics | nd | nd | 200,000 | 598 | 115 | ( |
| 1978 | Zimbabwe | Cross-sectional | Risk factors | 70,000 | 10,000 | nd | nd | nd |
( |
| 1988 | Mauritania | Case–control | Risk factors | nd | nd | nd | 224 | nd |
( |
| 1987–1989 | Senegal | Cohort | Molecular epidemiology | 1,715 | nd | 273 | 16 | nd |
( |
| 1997–1998 | Kenya | Cross-sectional | Ecology, risk factors and socioeconomics | 89,000 | 478 | 160,000 | 450 | 250 |
( |
| 1998 | Mauritania | Cross-sectional | Sero-epidemiology, entomology and virology | 343 | nd | 90 | 1 |
( | |
| 2000 | Saudi Arabia | Cross-sectional | Risk factors and ecology | >10,000 | 1,000 | 883 | 245 | 10 |
( |
| 2000–2001 | Yemeni | Cross-sectional | Risk factors and socioeconomics | 22,000 | 6,000 | 1,328 | 166 | 107 |
( |
| 2003 | Egypt | Cross-sectional | Risk factors and virology | nd | nd | 45 | 17 | nd |
( |
| 2007–2008 | Sudan | Cross-sectional | Risk factors and ecology | nd | nd | 75,000 | 222 | nd |
( |
| 2008–2009 | Madagascar | Cross-sectional | Epidemiology and socioeconomics | nd | nd | 10,000 (712) | 26 | nd |
( |
| 2006–2007 | Somalia | Cross-sectional | Risk factors, predictive modeling and ecology | nd | nd | 35,000 | 51 | 541 |
( |
| 2010–2011 | South Africa | Cross-sectional | Spatial and predictive modeling | 14,342 | 8,877 | 242 | 26 | nd |
( |
| 2012 | Mauritania | Cross-sectional | Risk factors, molecular diversity | nd | 343 | 41 | 17 | nd |
( |
nd=no documented estimates
=combined estimates.
Estimated cases in brackets are the reported.