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      A systematic review of Rift Valley Fever epidemiology 1931–2014

      review-article
      , BVM, MSc 1 , 2 , 3 , * , , BVM, MSc, PhD 4 , , BVM, MSc, PhD 5 , , BVM, MSc, PhD 2 , , BVM, MSc, PhD 3 , 6 , , BVM, MSc 7 , 8 , , BVM, MSc, PhD 9 , , BVM, MSc 8 , , BVM, PhD 3 , 6
      Infection Ecology & Epidemiology
      Co-Action Publishing
      Rift Valley Fever, spatiotemporal, modeling, epidemiology

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          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.

          Methodology

          Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we systematically searched for relevant RVF publications in repositories of the World Health Organization Library and Information Networks for Knowledge (WHOLIS), U.S Centers for Disease Control and Prevention (CDC), and Food and Agricultural Organization (FAO). Detailed searches were performed in Google Scholar, SpringerLink, and PubMed databases and included conference proceedings and books published from 1931 up to 31st January 2015.

          Results and discussion

          A total of 84 studies were included in this review; majority (50%) reported on common human and animal risk factors that included consumption of animal products, contact with infected animals and residing in low altitude areas associated with favorable climatic and ecological conditions for vector emergence. A total of 14 (16%) of the publications described RVF progressive spatial and temporal distribution and the use of risk modeling for timely prediction of imminent outbreaks. Using distribution maps, we illustrated the gradual spread and geographical extent of disease; we also estimated the disease burden using aggregate human mortalities and cumulative outbreak periods for endemic regions.

          Conclusion

          This review outlines common risk factors for RVF infections over wider geographical areas; it also emphasizes the role of spatial models in predicting RVF enzootics. It, therefore, explains RVF epidemiological status that may be used for design of targeted surveillance and control programs in endemic countries.

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          Most cited references96

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          Enzootic hepatitis or rift valley fever. An undescribed virus disease of sheep cattle and man from east africa

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            Rift Valley fever epidemic in Saudi Arabia: epidemiological, clinical, and laboratory characteristics.

            This cohort descriptive study summarizes the epidemiological, clinical, and laboratory characteristics of the Rift Valley fever (RVF) epidemic that occurred in Saudi Arabia from 26 August 2000 through 22 September 2001. A total of 886 cases were reported. Of 834 reported cases for which laboratory results were available, 81.9% were laboratory confirmed, of which 51.1% were positive for only RVF immunoglobulin M, 35.7% were positive for only RVF antigen, and 13.2% were positive for both. The mean age (+/- standard deviation) was 46.9+/-19.4 years, and the ratio of male to female patients was 4:1. Clinical and laboratory features included fever (92.6% of patients), nausea (59.4%), vomiting (52.6%), abdominal pain (38.0%), diarrhea (22.1%), jaundice (18.1%), neurological manifestations (17.1%), hemorrhagic manifestations (7.1%), vision loss or scotomas (1.5%), elevated liver enzyme levels (98%), elevated lactate dehydrogenase level (60.2%), thrombocytopenia (38.4%), leukopenia (39.7%), renal impairment or failure (27.8%), elevated creatine kinase level (27.3%), and severe anemia (15.1%). The mortality rate was 13.9%. Bleeding, neurological manifestations, and jaundice were independently associated with a high mortality rate. Patients with leukopenia had significantly a lower mortality rate than did those with a normal or high leukocyte count (2.3% vs. 27.9%; odds ratio, 0.09; 95% confidence interval, 0.01-0.63).
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              Climate and satellite indicators to forecast Rift Valley fever epidemics in Kenya.

              All known Rift Valley fever virus outbreaks in East Africa from 1950 to May 1998, and probably earlier, followed periods of abnormally high rainfall. Analysis of this record and Pacific and Indian Ocean sea surface temperature anomalies, coupled with satellite normalized difference vegetation index data, shows that prediction of Rift Valley fever outbreaks may be made up to 5 months in advance of outbreaks in East Africa. Concurrent near-real-time monitoring with satellite normalized difference vegetation data may identify actual affected areas.
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                Author and article information

                Journal
                Infect Ecol Epidemiol
                Infect Ecol Epidemiol
                IEE
                Infection Ecology & Epidemiology
                Co-Action Publishing
                2000-8686
                31 July 2015
                2015
                : 5
                : 10.3402/iee.v5.28024
                Affiliations
                [1 ]Department of Biomedical Sciences, Colorado State University, Fort Collins, CO, USA
                [2 ]Department of Public Health, Pharmacology and Toxicology, University of Nairobi, Nairobi, Kenya
                [3 ]Kenya Medical Research Institute, Nairobi, Kenya
                [4 ]Centers for Disease Control and Prevention, Nairobi, Kenya
                [5 ]Wangari Maathai Institute for Peace and Environmental Studies, University of Nairobi, Nairobi, Kenya
                [6 ]Paul G. Allen School for Global Animal Health, Washington State University, Pullman, WA, USA
                [7 ]Zoonotic Disease Unit, Nairobi, Kenya
                [8 ]Directorate of Veterinary Service, Nairobi, Kenya
                [9 ]International Livestock Research Institute, Nairobi, Kenya
                Author notes
                [* ]Correspondence to: Mark O. Nanyingi, Kenya Medical Research Institute, Nairobi, Kenya, Email: mnanyingi@ 123456kemricdc.org

                Responsible Editor: Åke Lundkvist, Uppsala University, Sweden.

                Article
                28024
                10.3402/iee.v5.28024
                4522434
                26234531
                17fe17c3-5816-44d3-87e2-8ab5b89a68df
                © 2015 Mark O. Nanyingi et al.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License, permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 30 March 2015
                : 15 June 2015
                : 10 July 2015
                Categories
                Review Article

                Infectious disease & Microbiology
                rift valley fever,spatiotemporal,modeling,epidemiology
                Infectious disease & Microbiology
                rift valley fever, spatiotemporal, modeling, epidemiology

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