Spatio-Temporal Variation of Malaria Incidence and Risk Factors in West Gojjam Zone, Northwest Ethiopia

被引：4

作者：

Tegegne, Eniyew ^{[1
]}

Gelaye, Kassahun Alemu ^{[2
]}

Dessie, Awrajaw ^{[2
]}

Shimelash, Alebachew ^{[1
]}

Asmare, Biachew ^{[3
]}

Deml, Yikeber Argachew ^{[4
]}

Lamore, Yonas ^{[1
]}

Temesgen, Tegegne ^{[1
]}

Demissie, Biruk ^{[5
]}

Teym, Abraham ^{[1
]}

机构：

[1] Debre Markos Univ, Coll Hlth Sci, Dept Environm Hlth, Debre Markos, Ethiopia

[2] Univ Gondar, Coll Med & Hlth Sci, Inst Publ Hlth, Gondar, Ethiopia

[3] Debre Markos Univ, Coll Hlth Sci, Dept Human Nutr, Debre Markos, Ethiopia

[4] Debre Markos Univ, Sch Med, Dept Biomed Sci, Debre Markos, Ethiopia

[5] Debre Tabor Univ, Coll Hlth Sci, Dept Environm Hlth, Debre Tabor, Ethiopia

来源：

ENVIRONMENTAL HEALTH INSIGHTS | 2022年 / 16卷

关键词：

Spatio-temporal variation; malaria incidence; risk factor; West Gojjam; Ethiopia; VILLAGE LEVEL; TRANSMISSION; HIGHLANDS; CLUSTERS;

D O I：

10.1177/11786302221095702

中图分类号：

R1 [预防医学、卫生学];

学科分类号：

1004 ; 120402 ;

摘要：

INTRODUCTION: Malaria is a life-threatening acute febrile illness which is affecting the lives of millions globally. Its distribution is characterized by spatial, temporal: and spatiotemporal heterogeneity. Detection of the space-time distribution and mapping high-risk areas is useful to target hot spots for effective intervention. METHODS: Time series cross sectional study was conducted using weekly malaria surveillance data obtained from Amhara Public Health Institute. Poisson model was fitted to determine the purely spatial, temporal, and space-time clusters using SaTScan (TM) 9.6 software. Spearman correlation. bivariate, and multivariable negative binomial regressions were used to analyze the relation of the climatic factors to count of malaria incidence. RESULT: Jabitenan, Quarit, Sekela, Bure, and Wonberma were high rate spatial cluster of malaria incidence hierarchically. Spatiotemporal clusters were detected. A temporal scan statistic identified 1 risk period from 1 July 2013 to 30 June 2015. The adjusted incidence rate ratio showed that monthly average temperature and monthly average rainfall were independent predictors for malaria incidence at all lag-months. Monthly average relative humidity was significant at 2 months lag. CONCLUSION: Malaria incidence had spatial, temporal. spatiotemporal variability in West Gojjam zone. Mean monthly temperature and rainfall were directly and negatively associated to count of malaria incidence respectively. Considering these space-time variations and risk factors (temperature and rainfall) would be useful for the prevention and control and ultimately achieve elimination.

引用

页数：10

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