Diagnostic testing of pediatric fevers: meta-analysis of 13 national surveys assessing influences of malaria endemicity and source of care on test uptake for febrile children under five years

Abstract

Background: In 2010, the World Health Organization revised guidelines to recommend diagnosis of all suspected malaria cases prior to treatment. There has been no systematic assessment of malaria test uptake for pediatric fevers at the population level as countries start implementing guidelines. We examined test use for pediatric fevers in relation to malaria endemicity and treatment-seeking behavior in multiple sub-Saharan African countries in initial years of implementation.

Methods and findings: We compiled data from national population-based surveys reporting fever prevalence, care-seeking and diagnostic use for children under five years in 13 sub-Saharan African countries in 2009-2011/12 (n = 105,791). Mixed-effects logistic regression models quantified the influence of source of care and malaria endemicity on test use after adjusting for socioeconomic covariates. Results were stratified by malaria endemicity categories: low (PfPR2-10<5%), moderate (PfPR2-10 5-40%), high (PfPR2-10>40%). Among febrile under-fives surveyed, 16.9% (95% CI: 11.8%-21.9%) were tested. Compared to hospitals, febrile children attending non-hospital sources (OR: 0.62, 95% CI: 0.56-0.69) and community health workers (OR: 0.31, 95% CI: 0.23-0.43) were less often tested. Febrile children in high-risk areas had reduced odds of testing compared to low-risk settings (OR: 0.51, 95% CI: 0.42-0.62). Febrile children in least poor households were more often tested than in poorest (OR: 1.63, 95% CI: 1.39-1.91), as were children with better-educated mothers compared to least educated (OR: 1.33, 95% CI: 1.16-1.54).

Conclusions: Diagnostic testing of pediatric fevers was low and inequitable at the outset of new guidelines. Greater testing is needed at lower or less formal sources where pediatric fevers are commonly managed, particularly to reach the poorest. Lower test uptake in high-risk settings merits further investigation given potential implications for diagnostic scale-up in these areas. Findings could inform continued implementation of new guidelines to improve access to and equity in point-of-care diagnostics use for pediatric fevers.

Figure 1. Flow chart of inclusion criteria for study.

Figure 2. Forest plot of test uptake at non-hospital sources versus hospitals in each country.

Figure legend: CI refers to confidence interval. Mixed-effects logistic regression models adjusted for data clustering and Table 3 covariates. AOR <1.0 indicates reduced odds of testing at non-hospital sources compared to hospitals.

Figure 3. Estimated pediatric fevers attending and tested by source of care in 13 countries in 2010.

Figure legend: All totals are given in ‘000 s.

Figure 4. Effect of maternal education on test uptake in different malaria endemicities.

Figure legend: ▴, Secondary or higher schooling versus no schooling; •, Primary schooling versus no schooling. Mixed-effects logistic regression model in pooled dataset of 13 surveys, adjusted for data clustering and Table 3 covariates. Stable transmission categories refer to low (PfPR_2–10<5%), moderate (PfPR_2–10 5%–40%) and high (PfPR_2–10>40%).