Malaria prevention in north-eastern Tanzania: patterns of expenditure and determinants of demand at the household level.
OBJECTIVE
This study aims to provide a better understanding of the amounts spent on different malaria prevention products and the determinants of these expenditures.


METHODS
1,601 households were interviewed about their expenditure on malaria mosquito nets in the past five years, net re-treatments in the past six months and other expenditures prevention in the past two weeks. Simple random sampling was used to select villages and streets while convenience sampling was used to select households. Expenditure was compared across bed nets, aerosols, coils, indoor spraying, using smoke, drinking herbs and cleaning outside environment.


RESULTS
68% of households owned at least one bed net and 27% had treated their nets in the past six months. 29% were unable to afford a net. Every fortnight, households spent an average of US $0.18 on nets and their treatment, constituting about 47% of total prevention expenditure. Sprays, repellents and coils made up 50% of total fortnightly expenditure (US$0.21). Factors positively related to expenditure were household wealth, years of education of household head, household head being married and rainy season. Poor quality roads and living in a rural area had a negative impact on expenditure.


CONCLUSIONS
Expenditure on bed nets and on alternative malaria prevention products was comparable. Poor households living in rural areas spend significantly less on all forms of malaria prevention compared to their richer counterparts. Breaking the cycle between malaria and poverty is one of the biggest challenges facing malaria control programmes in Africa.
McElroy
Brendan
B
Department of Economics, University College, Cork, Ireland. b.mcelroy@ucc.ie
Wiseman
Virginia
V
Matovu
Fred
F
Mwengee
William
W
D000293:Adolescent; D000328:Adult; D000818:Animals; D001512:Bedding and Linens / Q000191:economics* / Q000706:statistics & numerical data / Q000600:supply & distribution; D002648:Child; D003625:Data Collection; D004777:Environment; D005191:Family Characteristics; D005260:Female; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006301:Health Services Needs and Demand / Q000706:statistics & numerical data; D054625:Healthcare Disparities / Q000706:statistics & numerical data*; D006801:Humans; D007306:Insecticides / Q000191:economics*; D008288:Malaria / Q000191:economics / Q000453:epidemiology / Q000517:prevention & control*; D008297:Male; D008875:Middle Aged; D009032:Mosquito Control / Q000191:economics* / Q000379:methods; D011203:Poverty; D012621:Seasons; D012959:Socioeconomic Factors; D011795:Surveys and Questionnaires; D013636:Tanzania / Q000453:epidemiology; D055815:Young Adult
D007306:Insecticides