Economic and Resource Use Associated With Management of Malaria in Children Aged <5 Years in Sub-Saharan Africa: A Systematic Literature Review

Abstract

Background. Malaria is a major health, economic, and social burden in sub-Saharan Africa. Purpose. The objective is to help understanding the economic impact of malaria and informing estimates of the potential economic impact of malaria prevention. To achieve this, we conducted a systematic review of published information on health system costs, health care resource use, and household costs for the management of malaria episodes in children aged <5 years in sub-Saharan Africa. Data Sources and Study Selection. We conducted searches in Medline, EMBASE, and Cochrane Library for studies reporting data on economic cost or resource use associated with management of malaria in children aged <5 years in sub-Saharan Africa. Searches were limited to articles published in English or French between January 1, 2006, and September 1, 2016. Conference abstracts from 2014 to 2016 were hand-searched. Data Extraction and Data Synthesis. We identified 1846 publications, of which 17 met the selection criteria. The studies covered nine countries: The Democratic Republic of Congo, Ghana, Kenya, Malawi, Mozambique, Nigeria, Tanzania, Uganda, and Zambia. All costs were standardized to 2016 US dollars (US$). Seven studies estimated the costs of a malaria episode to health systems, and 10 publications plus one abstract reported household costs. The cost to the health system was US$1.94 to US$31.53 for outpatient malaria cases to US$20 to US$136 for inpatient cases. Families bear a large share of the burden through out-of-pocket payments of medical care and lost income due to time off work. Limitations. Data were missing for many countries and few comparisons could be made. Conclusions. Severe malaria is associated with much higher costs than uncomplicated malaria, and families bear a large share of the cost burden.

Estimating the Fraction of Severe Malaria among Malaria-Positive Children: Analysis of Household Surveys in 19 Malaria-Endemic Countries in Africa

“…Although the decision to seek care is ultimately made by the caregiver, it is highly influenced by factors such as the availability of government-based facilities, country wealth, cost of care, and education. 14,20,[25][26][27] Further exploration is needed into country and urban-rural variations in care-seeking and its association with severe malaria burden estimates. This study has several limitations.…”

Estimating cases of severe malaria at the population-level: Analysis of household surveys from 19 malaria endemic countries in Africa

“…By examining severe malaria cases at the household level, this analysis is more likely to include children whose caregivers have taken them to a healthcare facility but whose illness did not resolve or have not sought care for the child's illness. While the decision to seek care is ultimately decided by the caregiver, it is highly in uenced by factors such as the availability of government-based facilities, country wealth, cost of care, and education [14,[20][21][22][23]. Further exploration is needed into country and urban-rural variations in care-seeking and its association with severe malaria burden estimates.…”

Addressing child health inequity through case management of under-five malaria in Nigeria: A model-based extended cost-effectiveness analysis

“…[33,34,35] In Nigeria, non-medical and indirect costs often represent a high proportion of total expense associated with case management, especially for severe cases that require inpatient hospitalization and significant time spent away from work for caregiving. [19,36] While the FMCHP subsidized the direct medical costs of treatment, off-setting nonmedical and indirect costs will more effectively mitigate the economic burden of treating underfive malaria and could further incentivize service use. [19] To consider varying levels of financing capacity, three intervention scenarios were modeled: (1) a 50% subsidy of direct medical costs (50% DMC), (2) a full subsidy of direct medical costs (full DMC), and (3) a full subsidy of direct medical costs in addition to compensating individuals for non-medical and indirect costs through a voucher system (full DMC + NMC + IC).…”

“…. For example, in the full DMC + NMC +IC scenario, the wealthiest 20% of Nigerians would save about US$850,000 per US$1 million invested while the poorest 20% would save about US$780,000 per US$1 million invested (This is likely because higher income individuals incur higher indirect costs on account of productive time lost to caring for sick children-however, these costs are less likely to be catastrophic with increasing wealth [36]. A full DMC + NMC + IC subsidy targeted towards the poor would result in the greatest number of deaths averted and cases of CHE averted while averting OOP expenditure most equitably.While a full DMC + NMC + IC subsidy would avert US$63.1 million more OOP expenditure than a full DMC subsidy, we found almost no difference in incremental cases of CHE averted between the two scenarios.…”