A statistical model of Rift Valley fever activity in Egypt

John M. Drake, Ali N. Hassan, John C Beier

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Rift Valley fever (RVF) is a viral disease of animals and humans and a global public health concern due to its ecological plasticity, adaptivity, and potential for spread to countries with a temperate climate. In many places, outbreaks are episodic and linked to climatic, hydrologic, and socioeconomic factors. Although outbreaks of RVF have occurred in Egypt since 1977, attempts to identify risk factors have been limited. Using a statistical learning approach (lasso-regularized generalized linear model), we tested the hypotheses that outbreaks in Egypt are linked to (1) River Nile conditions that create a mosquito vector habitat, (2) entomologic conditions favorable to transmission, (3) socio-economic factors (Islamic festival of Greater Bairam), and (4) recent history of transmission activity. Evidence was found for effects of rainfall and river discharge and recent history of transmission activity. There was no evidence for an effect of Greater Bairam. The model predicted RVF activity correctly in 351 of 358 months (98.0%). This is the first study to statistically identify risk factors for RVF outbreaks in a region of unstable transmission.

Original languageEnglish
Pages (from-to)251-259
Number of pages9
JournalJournal of Vector Ecology
Volume38
Issue number2
DOIs
StatePublished - Dec 1 2013

Fingerprint

Rift Valley fever
rift zone
statistical models
Egypt
socioeconomic factors
risk factor
risk factors
viral diseases of animals and humans
Nile River
hydrologic factors
viral disease
festival
climatic factors
history
mosquito
river discharge
temperate zones
plasticity
public health
Culicidae

Keywords

  • Egypt
  • Forecast
  • Regularized regression
  • Rift valley fever

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecology

Cite this

A statistical model of Rift Valley fever activity in Egypt. / Drake, John M.; Hassan, Ali N.; Beier, John C.

In: Journal of Vector Ecology, Vol. 38, No. 2, 01.12.2013, p. 251-259.

Research output: Contribution to journalArticle

Drake, John M. ; Hassan, Ali N. ; Beier, John C. / A statistical model of Rift Valley fever activity in Egypt. In: Journal of Vector Ecology. 2013 ; Vol. 38, No. 2. pp. 251-259.
@article{1434b004191849448c4457c0e495f504,
title = "A statistical model of Rift Valley fever activity in Egypt",
abstract = "Rift Valley fever (RVF) is a viral disease of animals and humans and a global public health concern due to its ecological plasticity, adaptivity, and potential for spread to countries with a temperate climate. In many places, outbreaks are episodic and linked to climatic, hydrologic, and socioeconomic factors. Although outbreaks of RVF have occurred in Egypt since 1977, attempts to identify risk factors have been limited. Using a statistical learning approach (lasso-regularized generalized linear model), we tested the hypotheses that outbreaks in Egypt are linked to (1) River Nile conditions that create a mosquito vector habitat, (2) entomologic conditions favorable to transmission, (3) socio-economic factors (Islamic festival of Greater Bairam), and (4) recent history of transmission activity. Evidence was found for effects of rainfall and river discharge and recent history of transmission activity. There was no evidence for an effect of Greater Bairam. The model predicted RVF activity correctly in 351 of 358 months (98.0{\%}). This is the first study to statistically identify risk factors for RVF outbreaks in a region of unstable transmission.",
keywords = "Egypt, Forecast, Regularized regression, Rift valley fever",
author = "Drake, {John M.} and Hassan, {Ali N.} and Beier, {John C}",
year = "2013",
month = "12",
day = "1",
doi = "10.1111/j.1948-7134.2013.12038.x",
language = "English",
volume = "38",
pages = "251--259",
journal = "Journal of Vector Ecology",
issn = "1081-1710",
publisher = "Society for Vector Ecology",
number = "2",

}

TY - JOUR

T1 - A statistical model of Rift Valley fever activity in Egypt

AU - Drake, John M.

AU - Hassan, Ali N.

AU - Beier, John C

PY - 2013/12/1

Y1 - 2013/12/1

N2 - Rift Valley fever (RVF) is a viral disease of animals and humans and a global public health concern due to its ecological plasticity, adaptivity, and potential for spread to countries with a temperate climate. In many places, outbreaks are episodic and linked to climatic, hydrologic, and socioeconomic factors. Although outbreaks of RVF have occurred in Egypt since 1977, attempts to identify risk factors have been limited. Using a statistical learning approach (lasso-regularized generalized linear model), we tested the hypotheses that outbreaks in Egypt are linked to (1) River Nile conditions that create a mosquito vector habitat, (2) entomologic conditions favorable to transmission, (3) socio-economic factors (Islamic festival of Greater Bairam), and (4) recent history of transmission activity. Evidence was found for effects of rainfall and river discharge and recent history of transmission activity. There was no evidence for an effect of Greater Bairam. The model predicted RVF activity correctly in 351 of 358 months (98.0%). This is the first study to statistically identify risk factors for RVF outbreaks in a region of unstable transmission.

AB - Rift Valley fever (RVF) is a viral disease of animals and humans and a global public health concern due to its ecological plasticity, adaptivity, and potential for spread to countries with a temperate climate. In many places, outbreaks are episodic and linked to climatic, hydrologic, and socioeconomic factors. Although outbreaks of RVF have occurred in Egypt since 1977, attempts to identify risk factors have been limited. Using a statistical learning approach (lasso-regularized generalized linear model), we tested the hypotheses that outbreaks in Egypt are linked to (1) River Nile conditions that create a mosquito vector habitat, (2) entomologic conditions favorable to transmission, (3) socio-economic factors (Islamic festival of Greater Bairam), and (4) recent history of transmission activity. Evidence was found for effects of rainfall and river discharge and recent history of transmission activity. There was no evidence for an effect of Greater Bairam. The model predicted RVF activity correctly in 351 of 358 months (98.0%). This is the first study to statistically identify risk factors for RVF outbreaks in a region of unstable transmission.

KW - Egypt

KW - Forecast

KW - Regularized regression

KW - Rift valley fever

UR - http://www.scopus.com/inward/record.url?scp=84887511333&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84887511333&partnerID=8YFLogxK

U2 - 10.1111/j.1948-7134.2013.12038.x

DO - 10.1111/j.1948-7134.2013.12038.x

M3 - Article

C2 - 24581353

AN - SCOPUS:84887511333

VL - 38

SP - 251

EP - 259

JO - Journal of Vector Ecology

JF - Journal of Vector Ecology

SN - 1081-1710

IS - 2

ER -