AbstractBackgroundThe malaria test positivity rate (TPR) is increasingly used as an indicator of malaria morbidity because TPR is based on laboratory-confirmed cases and is simple to incorporate into existing surveillance systems. However, temporal trends in TPR may reflect changes in factors associated with malaria rather than true changes in malaria morbidity. This study examines the effects of age, area of residence and diagnostic test on TPR at two health facilities in regions of Uganda with differing malaria endemicity.MethodsThe analysis included data from diagnostic blood smears performed at health facilities in Walukuba and Aduku between January 2009 and December 2010. The associations between age and time and between age and TPR were evaluated independently to determine the potential for age to confound temporal trends in TPR. Subsequently, differences between observed TPR and TPR adjusted for age were compared to determine if confounding was present. A similar analysis was performed for area of residence. Temporal trends in observed TPR were compared to trends in TPR expected using rapid diagnostic tests, which were modelled based upon sensitivity and specificity in prior studies.ResultsAge was independently associated with both TPR and time at both sites. At Aduku, age-adjusted TPR increased relative to observed TPR due to the association between younger age and TPR and the gradual increase in age distribution. At Walukuba, there were no clear differences between observed and age-adjusted TPR. Area of residence was independently associated with both TPR and time at both sites, though there were no clear differences in temporal trends in area of residence-adjusted TPR and observed TPR at either site. Expected TPR with pLDH- and HRP-2-based rapid diagnostic tests (RDTs) was higher than observed TPR at all time points at both sites.ConclusionsAdjusting for potential confounders such as age and area of residence can ensure that temporal trends in TPR due to confounding are not mistakenly ascribed to true changes in malaria morbidity. The potentially large effect of diagnostic test on TPR can be accounted for by calculating and adjusting for the sensitivity and specificity of the test used.

The potential spread of antimalarial drug resistance to Africa, in particular for artemisinins and key partner drugs, is a major concern. We surveyed Plasmodium falciparum genetic markers associated with drug sensitivity on 3 occasions at ∼6-month intervals in 2016 and 2017 at 10 sites representing a range of epidemiological settings in Uganda. For putative drug transporters, we found continued evolution toward wild-type sequences associated with increased sensitivity to chloroquine. For pfcrt K76T, by 2017 the prevalence of the wild type was >60% at all sites and >90% at 6 sites. For the pfmdr1 N86Y and D1246Y alleles, wild type prevalence ranged from 80 to 100%. We found low prevalence of K13 propeller domain mutations, which are associated with artemisinin resistance in Asia, but one mutation previously identified in northern Uganda, 675V, was seen in 2.0% of samples, including 5.5% of those from the 3 northernmost sites. Amplification of the pfmdr1 and plasmepsin2 genes, associated elsewhere with decreased sensitivity to lumefantrine and piperaquine, respectively, was seen in <1% of samples. For the antifolate targets pfdhfr and pfdhps, 5 mutations previously associated with resistance were very common, and the pfdhfr 164L and pfdhps 581G mutations associated with higher-level resistance were seen at multiple sites, although prevalence did not clearly increase over time. Overall, changes were consistent with the selective pressure of the national treatment regimen, artemether-lumefantrine, with increased sensitivity to chloroquine, and with poor efficacy of antifolates. Strong evidence for resistance to artemisinins was not seen. Continued surveillance of markers that predict antimalarial drug sensitivity is warranted.

The intensification of control interventions has led to marked reductions in malaria burden in some settings, but not others. To provide a comprehensive description of malaria epidemiology in Uganda, we conducted surveillance studies over 24 months in 100 houses randomly selected from each of three subcounties: Walukuba (peri-urban), Kihihi (rural), and Nagongera (rural). Annual entomological inoculation rate (aEIR) was estimated from monthly Centers for Disease Control and Prevention (CDC) light trap mosquito collections. Children aged 0.5-10 years were provided long-lasting insecticidal nets (LLINs) and followed for measures of parasite prevalence, anemia and malaria incidence. Estimates of aEIR were 2.8, 32.0, and 310 infectious bites per year, and estimates of parasite prevalence 7.4%, 9.3%, and 28.7% for Walukuba, Kihihi, and Nagongera, respectively. Over the 2-year study, malaria incidence per person-years decreased in Walukuba (0.51 versus 0.31, P = 0.001) and increased in Kihihi (0.97 versus 1.93, P < 0.001) and Nagongera (2.33 versus 3.30, P < 0.001). Of 2,582 episodes of malaria, only 8 (0.3%) met criteria for severe disease. The prevalence of anemia was low and not associated with transmission intensity. In our cohorts, where LLINs and prompt effective treatment were provided, the risk of complicated malaria and anemia was extremely low. However, malaria incidence was high and increased over time at the two rural sites, suggesting improved community-wide coverage of LLIN and additional malaria control interventions are needed in Uganda.

Background

Malaria control using long-lasting insecticidal nets (LLINs) and indoor residual spraying of insecticide (IRS) has been associated with reduced transmission throughout Africa. However, the impact of transmission reduction on the age distribution of malaria cases remains unclear.

Methods

Over a 10-year period (January 2009 to July 2018), outpatient surveillance data from four health facilities in Uganda were used to estimate the impact of control interventions on temporal changes in the age distribution of malaria cases using multinomial regression. Interventions included mass distribution of LLINs at all sites and IRS at two sites.

Results

Overall, 896,550 patient visits were included in the study; 211,632 aged < 5 years, 171,166 aged 5-15 years and 513,752 > 15 years. Over time, the age distribution of patients not suspected of malaria and those malaria negative either declined or remained the same across all sites. In contrast, the age distribution of suspected and confirmed malaria cases increased across all four sites. In the two LLINs-only sites, the proportion of malaria cases in < 5 years decreased from 31 to 16% and 35 to 25%, respectively. In the two sites receiving LLINs plus IRS, these proportions decreased from 58 to 30% and 64 to 47%, respectively. Similarly, in the LLINs-only sites, the proportion of malaria cases > 15 years increased from 40 to 61% and 29 to 39%, respectively. In the sites receiving LLINs plus IRS, these proportions increased from 19 to 44% and 18 to 31%, respectively.

Conclusions

These findings demonstrate a shift in the burden of malaria from younger to older individuals following implementation of successful control interventions, which has important implications for malaria prevention, surveillance, case management and control strategies.