Spatial and temporal variations of malaria epidemic risk in Ethiopia: factors involved and implications

Abeku, Tarekegn A.; Oortmarssen, G. J. Van; Borsboom, Gerard; Vlas, Sake J. de; Habbema, J. Dik F.

doi:10.1016/s0001-706x(03)00123-2

Cited by 162 publications

(173 citation statements)

References 4 publications

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“…24 Instead, in other malaria-endemic areas, mean or minimum temperatures were the best predictors of clinical malaria. 25,26 However, most such analyses have been carried out at monthly time scale and were not able to provide a time lag on a weekly scale. More precise results with a resolution of weeks such as this study are rarely reported.…”

Section: Discussionmentioning

confidence: 99%

Modeling the Relationship between Precipitation and Malaria Incidence in Children from a Holoendemic Area in Ghana

Krefis¹,

Schwarz²,

Krüger³

et al. 2011

The American Society of Tropical Medicine and Hygiene

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Climatic factors influence the incidence of vector-borne diseases such as malaria. They modify the abundance of mosquito populations, the length of the extrinsic parasite cycle in the mosquito, the malarial dynamics, and the emergence of epidemics in areas of low endemicity. The objective of this study was to investigate temporal associations between weekly malaria incidence in 1,993 children < 15 years of age and weekly rainfall. A time series analysis was conducted by using cross-correlation function and autoregressive modeling. The regression model showed that the level of rainfall predicted the malaria incidence after a time lag of 9 weeks (mean = 60 days) and after a time lag between one and two weeks. The analyses provide evidence that high-resolution precipitation data can directly predict malaria incidence in a highly endemic area. Such models might enable the development of early warning systems and support intervention measures.

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Section: Discussionmentioning

confidence: 99%

Modeling the Relationship between Precipitation and Malaria Incidence in Children from a Holoendemic Area in Ghana

Krefis¹,

Schwarz²,

Krüger³

et al. 2011

The American Society of Tropical Medicine and Hygiene

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“…In highland areas of Kenya, malaria admissions have been associated with rainfall and unusually high maximum temperatures 3-4 months previously (Githeko and Ndegwa, 2001). An analysis of malaria morbidity data for the period from the late 1980s until the early 1990s from 50 sites across Ethiopia found that epidemics were associated with high minimum temperatures in the preceding months (Abeku et al, 2003). An analysis of data from seven highland sites in East Africa reported that short-term climate variability played a more important role than long-term trends in initiating malaria epidemics (Zhou et al, 2004(Zhou et al, , 2005, although the method used to test this hypothesis has been challenged (Hay et al, 2005).…”

Section: 82]mentioning

confidence: 99%

Resistance and Resilience of A Stream Salamander To Supraseasonal Drought

2012

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“…Several epidemics have been reported since then. Abnormal transmission of unusual proportions has affected the highlands and highland-fringe areas in 1988 and 1991-92 which was associated with abnormally increased minimum temperature (Abeku et al 2003). More recently, epidemics have occurred in the highlands during the second half of the last decade ; in particular a widespread epidemic in 1998 was largely attributed to an El Niñ o event (unpublished data).…”

Section: Introductionmentioning

confidence: 99%

Effects of meteorological factors on epidemic malaria in Ethiopia: a statistical modelling approach based on theoretical reasoning

et al. 2004

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S U M M A R YThis study was conducted to quantify the association between meteorological variables and incidence of Plasmodium falciparum in areas with unstable malaria transmission in Ethiopia. We used morbidity data pertaining to microscopically confirmed cases reported from 35 sites throughout Ethiopia over a period of approximately 6-7 years. A model was developed reflecting biological relationships between meteorological and morbidity variables. A model that included rainfall 2 and 3 months earlier, mean minimum temperature of the previous month and P. falciparum case incidence during the previous month was fitted to morbidity data from the various areas. The model produced similar percentages of overestimation (19 . 7 % of predictions exceeded twice the observed values) and under-estimation (18 . 6% were less than half the observed values). Inclusion of maximum temperature did not improve the model. The model performed better in areas with relatively high or low incidence (>85 % of the total variance explained) than those with moderate incidence (55-85% of the total variance explained). The study indicated that a dynamic immunity mechanism is needed in a prediction model. The potential usefulness and drawbacks of the modelling approach in studying the weather-malaria relationship are discussed, including a need for mechanisms that can adequately handle temporal variations in immunity to malaria.

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Spatial and temporal variations of malaria epidemic risk in Ethiopia: factors involved and implications

Cited by 162 publications

References 4 publications

Modeling the Relationship between Precipitation and Malaria Incidence in Children from a Holoendemic Area in Ghana

Modeling the Relationship between Precipitation and Malaria Incidence in Children from a Holoendemic Area in Ghana

Resistance and Resilience of A Stream Salamander To Supraseasonal Drought

Effects of meteorological factors on epidemic malaria in Ethiopia: a statistical modelling approach based on theoretical reasoning

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