Is malaria a disease of poverty? A review of the literature (original) (raw)
The American journal of tropical medicine and hygiene, 2007
Malaria's relationship with socioeconomic status at the macroeconomic level has been established. This is the first study to explore this relationship at the microeconomic (household) level and estimate the direction of association. Malaria prevalence was measured by parasitemia, and household socioeconomic status was measured using an asset based index. Results from an instrumental variable probit model suggest that socioeconomic status is negatively associated with malaria parasitemia. Other variables that are significantly associated with parasitemia include age of the individual, use of a mosquito net on the night before interview, the number of people living in the household, whether the household was residing at their farm home at the time of interview, household wall construction, and the region of residence. Matching estimators indicate that malaria parasitemia is associated with reduced household socioeconomic status.
Do malaria control interventions reach the poor? A view through the equity lens
The American journal of tropical medicine and hygiene, 2004
Malaria, more than any other disease of major public health importance in developing countries, disproportionately affects poor people, with 58% of malaria cases occurring in the poorest 20% of the world's population. If malaria control interventions are to achieve their desired impact, they must reach the poorest segments of the populations of developing countries. Unfortunately, a growing body of evidence from benefit-incidence analyses has demonstrated that many public health interventions that were designed to aid the poor are not reaching their intended target. For example, the poorest 20% of people in selected developing countries were as much as 2.5 times less likely to receive basic public health services as the least-poor 20%. In the field of malaria control, a small number of studies have begun to shed light on differences by wealth status of malaria burden and of access to treatment and prevention services. These early studies found no clear difference in fever incide...
No influence of socioeconomic factors on severe malarial anaemia, hyperparasitaemia or reinfection
Transactions of the Royal Society of Tropical Medicine and Hygiene
Malaria is responsible for nearly 500 million clinical cases per year, only a small proportion of whom will become severely ill. Socioeconomic risk factors may play a role in the development of severe malaria in African children and in their susceptibility to reinfection. In Gabon, 100 children suffering from severe malaria, defined as hyperparasitaemia and/or severe anaemia, were matched for sex, age and provenance to 100 children with mild malaria. Socioeconomic factors were assessed using a standard questionnaire and compared between the 2 groups. The children were followed-up and the time to first reinfection was recorded. No significant influence of socioeconomic factors could be detected on the severity of disease or the time to first reinfection. Socioeconomic factors are not major determinants of severe malarial anaemia and hyperparasitaemia in children in Gabon.
SOCIOECONOMIC AND ENVIRONMENTAL DETERMINANTS OF MALARIA
Malaria and other mosquito borne diseases impose health problem particularly in Tropics. Transmission of malaria depends on both climate and socioeconomic variables. Our study is a survey among the population of Chitpur and
American Journal of Tropical Medicine and Hygiene, 2016
Socioeconomic position (SEP) is an important risk factor for malaria, but there is no consensus on how to measure SEP in malaria studies. We evaluated the relative strength of four indicators of SEP in predicting malaria risk in Nagongera, Uganda. 318 children resident in 100 households were followed for 36 months to measure parasite prevalence routinely every three months and malaria incidence by passive case detection. Household SEP was determined using: (1) two wealth indices, (2) income, (3) occupation and (4) education. Wealth Index I (reference) included only asset ownership variables. Wealth Index II additionally included food security and house construction variables, which may directly affect malaria. In multivariate analysis, only Wealth Index II and income were associated with the human biting rate, only Wealth Indices I and II were associated with parasite prevalence and only caregiver's education was associated with malaria incidence. This is the first evaluation of metrics beyond wealth and consumption indices for measuring the association between SEP and malaria. The wealth index still predicted malaria risk after excluding variables directly associated with malaria, but the strength of association was lower. In this setting, wealth indices, income and education were stronger predictors of socioeconomic differences in malaria risk than occupation.
Identifying Socio-Economic factors Associated with Malaria Infection in Birnin Kebbi, Nigeria
Continental J. Biological Sciences - Danladi and Suleiman - 14 (1): 9 – 15, 2021
Malaria has long been identified as a major cause of morbidity and mortality, in Nigeria. Data explaining the potential effect of socioeconomic variables on malaria risk, are scantly available in many places. This study was conducted to assess the effect of socioeconomic factors on the occurrence of malaria among study population in Birnin Kebbi, Nigeria. Structured questionnaires were administered to gather relevant baseline information about the study population. Blood samples were collected and tested for malaria using rapid diagnostic test kit (RTD). Persons who cannot read or write had more malaria infections to a significant level than those who were literate (Cannot read or write: 28.0%, vs Can read and write: 18.0%; P = 0.042). There were more cases recorded among farmers (29.5%), than civil servants (16.8%), business and unemployed persons (20.6% each). However, no significant disparity was observed in the distribution among various occupations (P = 0.244). More cases of malaria (24.7%) were encountered among low income earners per month (<N5, 000) than those who earned more per month (>N5, 000), with no significant variation (P = 0.210) in malaria burdens. Illiteracy among study participants has been identified as an important predictor of high malaria burdens in Birnin Kebbi. Public policy measures that can reduce inequalities in health coverage, and promote educational and economic opportunities of the poor may result in the reduction of the burden of malaria in the study area.
Malaria Journal
Background African region accounts for 95% of all malaria cases and 96% of malaria deaths with under-five children accounting for 80% of all deaths in the region. This study assessed the socioeconomic determinants of malaria prevalence and provide evidence on the socioeconomic profile of malaria infection among under-five children in 11 SSA countries. Methods This study used data from the 2010 to 2020 Demographic and Health Survey (DHS). The survey used a two-stage stratified-cluster sampling design based on the sampling frame of the population and housing census of countries included. Statistical analyses relied on Pearson’s χ2, using the CHAID decision-tree algorithm and logistic regression implemented in R V.4.6. Results Of 8547 children considered, 24.2% (95% confidence interval CI 23.4–25.05%) had malaria infection. Also, the prevalence of malaria infection seems to increase with age. The following variables are statistically associated with the prevalence of malaria infection ...
State of inequality in malaria intervention coverage in sub-Saharan African countries
BMC medicine, 2017
Scale-up of malaria interventions over the last decade have yielded a significant reduction in malaria transmission and disease burden in sub-Saharan Africa. We estimated economic gradients in the distribution of these efforts and of their impacts within and across endemic countries. Using Demographic and Health Surveys we computed equity metrics to characterize the distribution of malaria interventions in 30 endemic countries proxying economic position with an asset-wealth index. Gradients were summarized in a concentration index, tabulated against level of coverage, and compared among interventions, across countries, and against respective trends over the period 2005-2015. There remain broad differences in coverage of malaria interventions and their distribution by wealth within and across countries. In most, economic gradients are lacking or favor the poorest for vector control; malaria services delivered through the formal healthcare sector are much less equitable. Scale-up of i...