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Summary Background Long-lasting insecticidal nets (LLINs) are the primary malaria prevention tool, but their effectiveness is threatened by pyrethroid resistance. We embedded a pragmatic cluster-randomised trial into Uganda's national LLIN campaign to compare conventional LLINs with those containing piperonyl butoxide (PBO), a synergist that can partially restore pyrethroid susceptibility in mosquito vectors. Methods 104 health sub-districts, from 48 districts in Uganda, were randomly assigned to LLINs with PBO (PermaNet 3.0 and Olyset Plus) and conventional LLINs (PermaNet 2.0 and Olyset Net) by proportionate randomisation using an iterative process. At baseline 6, 12, and 18 months after LLIN distribution, cross-sectional surveys were done in 50 randomly selected households per cluster (5200 per survey); a subset of ten households per cluster (1040 per survey) were randomly selected for entomological surveys. The primary outcome was parasite prevalence by microscopy in children aged 2–10 years, assessed in the as-treated population at 6, 12, and 18 months. This trial is registered with ISRCTN, ISRCTN17516395. Findings LLINs were delivered to households from March 25, 2017, to March 18, 2018, 32 clusters were randomly assigned to PermaNet 3.0, 20 to Olyset Plus, 37 to PermaNet 2.0, and 15 to Olyset Net. In the as-treated analysis, three clusters were excluded because no dominant LLIN was received, and four clusters were reassigned, resulting in 49 PBO LLIN clusters (31 received PermaNet 3.0 and 18 received Olyset Plus) and 52 non-PBO LLIN clusters (39 received PermaNet 2.0 and 13 received Olyset Net). At 6 months, parasite prevalence was 11% (386/3614) in the PBO group compared with 15% (556/3844) in the non-PBO group (prevalence ratio [PR] adjusted for baseline values 0·74, 95% CI 0·62–0·87; p=0·0003). Parasite prevalence was similar at month 12 (11% vs 13%; PR 0·73, 95% CI 0·63–0·85; p=0·0001) and month 18 (12% vs 14%; PR 0·84, 95% CI 0·72–0·98; p=0·029). Interpretation In Uganda, where pyrethroid resistance is high, PBO LLINs reduced parasite prevalence more effectively than did conventional LLINs for up to 18 months. This study provides evidence needed to support WHO's final recommendation on use of PBO LLINs. Funding The Against Malaria Foundation, UK Department for International Development, Innovative Vector Control Consortium, and Bill and Melinda Gates Foundation.

Background Malaria surveillance is critical for monitoring changes in malaria morbidity over time. National Malaria Control Programmes often rely on surrogate measures of malaria incidence, including the test positivity rate (TPR) and total laboratory confirmed cases of malaria (TCM), to monitor trends in malaria morbidity. However, there are limited data on the accuracy of TPR and TCM for predicting temporal changes in malaria incidence, especially in high burden settings. Methods This study leveraged data from 5 malaria reference centres (MRCs) located in high burden settings over a 15-month period from November 2018 through January 2020 as part of an enhanced health facility-based surveillance system established in Uganda. Individual level data were collected from all outpatients including demographics, laboratory test results, and village of residence. Estimates of malaria incidence were derived from catchment areas around the MRCs. Temporal relationships between monthly aggregate measures of TPR and TCM relative to estimates of malaria incidence were examined using linear and exponential regression models. Results A total of 149,739 outpatient visits to the 5 MRCs were recorded. Overall, malaria was suspected in 73.4% of visits, 99.1% of patients with suspected malaria received a diagnostic test, and 69.7% of those tested for malaria were positive. Temporal correlations between monthly measures of TPR and malaria incidence using linear and exponential regression models were relatively poor, with small changes in TPR frequently associated with large changes in malaria incidence. Linear regression models of temporal changes in TCM provided the most parsimonious and accurate predictor of changes in malaria incidence, with adjusted R2 values ranging from 0.81 to 0.98 across the 5 MRCs. However, the slope of the regression lines indicating the change in malaria incidence per unit change in TCM varied from 0.57 to 2.13 across the 5 MRCs, and when combining data across all 5 sites, the R2 value reduced to 0.38. Conclusions In high malaria burden areas of Uganda, site-specific temporal changes in TCM had a strong linear relationship with malaria incidence and were a more useful metric than TPR. However, caution should be taken when comparing changes in TCM across sites.

Background Surveillance data are essential for malaria control, but quality is often poor. The aim of the study was to evaluate the effectiveness of the novel combination of training plus an innovative quality improvement method—collaborative improvement (CI)—on the quality of malaria surveillance data in Uganda. Methods The intervention (training plus CI, or TCI), including brief in-service training and CI, was delivered in 5 health facilities (HFs) in Kayunga District from November 2015 to August 2016. HF teams monitored data quality, conducted plan-do-study-act cycles to test changes, attended periodic learning sessions, and received CI coaching. An independent evaluation was conducted to assess data completeness, accuracy, and timeliness. Using an interrupted time series design without a separate control group, data were abstracted from 156,707 outpatient department (OPD) records, laboratory registers, and aggregated monthly reports (MR) for 4 time periods: baseline—12 months, TCI scale-up—5 months; CI implementation—9 months; post-intervention—4 months. Monthly OPD register completeness was measured as the proportion of patient records with a malaria diagnosis with: (1) all data fields completed, and (2) all clinically-relevant fields completed. Accuracy was the relative difference between: (1) number of monthly malaria patients reported in OPD register versus MR, and (2) proportion of positive malaria tests reported in the laboratory register versus MR. Data were analysed with segmented linear regression modelling. Results Data completeness increased substantially following TCI. Compared to baseline, all-field completeness increased by 60.1%-points (95% confidence interval [CI]: 46.9–73.2%) at mid-point, and clinically-relevant completeness increased by 61.6%-points (95% CI: 56.6–66.7%). A relative − 57.4%-point (95% confidence interval: − 105.5, − 9.3%) change, indicating an improvement in accuracy of malaria test positivity reporting, but no effect on data accuracy for monthly malaria patients, were observed. Cost per additional malaria patient, for whom complete clinically-relevant data were recorded in the OPD register, was $3.53 (95% confidence interval: $3.03, $4.15). Conclusions TCI improved malaria surveillance completeness considerably, with limited impact on accuracy. Although these results are promising, the intervention’s effectiveness should be evaluated in more HFs, with longer follow-up, ideally in a randomized trial, before recommending CI for wide-scale use.

Global malaria burden is reducing with effective control interventions, and surveillance is vital to maintain progress. Health management information system (HMIS) data provide a powerful surveillance tool; however, its estimates of burden need to be better understood for effectiveness. We aimed to investigate the relationship between HMIS and cohort incidence rates and identify sources of bias in HMIS-based incidence. Malaria incidence was estimated using HMIS data from 15 health facilities in three subcounties in Uganda. This was compared with a gold standard of representative cohort studies conducted in children aged 0.5 to < 11 years, followed concurrently in these sites. Between October 2011 and September 2014, 153,079 children were captured through HMISs and 995 followed up through enhanced community cohorts in Walukuba, Kihihi, and Nagongera subcounties. Although HMISs substantially underestimated malaria incidence in all sites compared with data from the cohort studies, there was a strong linear relationship between these rates in the lower transmission settings (Walukuba and Kihihi), but not the lowest HMIS performance highest transmission site (Nagongera), with calendar year as a significant modifier. Although health facility accessibility, availability, and recording completeness were associated with HMIS incidence, they were not significantly associated with bias in estimates from any site. Health management information systems still require improvements; however, their strong predictive power of unbiased malaria burden when improved highlights the important role they could play as a cost-effective tool for monitoring trends and estimating impact of control interventions. This has important implications for malaria control in low-resource, high-burden countries.

Background As global progress to reduce malaria transmission continues, it is increasingly important to track changes in malaria incidence rather than prevalence. Risk estimates for Africa have largely underutilized available health management information systems (HMIS) data to monitor trends. This study uses national HMIS data, together with environmental and geographical data, to assess spatial-temporal patterns of malaria incidence at facility catchment level in Uganda, over a recent 5-year period. Methods Data reported by 3446 health facilities in Uganda, between July 2015 and September 2019, was analysed. To assess the geographic accessibility of the health facilities network, AccessMod was employed to determine a three-hour cost-distance catchment around each facility. Using confirmed malaria cases and total catchment population by facility, an ecological Bayesian conditional autoregressive spatial-temporal Poisson model was fitted to generate monthly posterior incidence rate estimates, adjusted for caregiver education, rainfall, land surface temperature, night-time light (an indicator of urbanicity), and vegetation index. Results An estimated 38.8 million (95% Credible Interval [CI]: 37.9–40.9) confirmed cases of malaria occurred over the period, with a national mean monthly incidence rate of 20.4 (95% CI: 19.9–21.5) cases per 1000, ranging from 8.9 (95% CI: 8.7–9.4) to 36.6 (95% CI: 35.7–38.5) across the study period. Strong seasonality was observed, with June–July experiencing highest peaks and February–March the lowest peaks. There was also considerable geographic heterogeneity in incidence, with health facility catchment relative risk during peak transmission months ranging from 0 to 50.5 (95% CI: 49.0–50.8) times higher than national average. Both districts and health facility catchments showed significant positive spatial autocorrelation; health facility catchments had global Moran’s I = 0.3 (p p Conclusion Findings showed clear countrywide spatial-temporal patterns with clustering of malaria risk across districts and health facility catchments within high risk regions, which can facilitate targeting of interventions to those areas at highest risk. Moreover, despite high and perennial transmission, seasonality for malaria incidence highlights the potential for optimal and timely implementation of targeted interventions.

Background Intermittent preventive treatment (IPT) of malaria is recommended as policy for certain high-risk populations, but not currently for schoolchildren. A cluster-randomized trial was conducted to evaluate the effect of IPT with dihydroartemisinin–piperaquine (DP) on primary schoolchildren in Jinja, Uganda. Results of the impact of IPT of schoolchildren on community-level transmission have been reported previously. Here, secondary outcomes from a school-based survey are presented. Methods Eighty-four clusters (one primary school plus 100 households) were randomized to intervention and control (1:1 ratio). Participants from intervention schools received monthly IPT with DP for up to 6 rounds (June–December 2014). At endline (November–December 2014), randomly selected children from all 84 schools were surveyed (13 per school) and thick blood smears were done. Those with fever or history of fever were tested with rapid diagnostic tests (RDTs) for malaria. Haemoglobin was measured in every fifth participant. Outcome measures included prevalence of asexual parasites and gametocytes (by microscopy), and prevalence of anaemia. Prevalence outcomes were analysed using generalized linear Poisson models with log link function, incorporating a cluster-level random intercept and quantified using prevalence risk ratios. Results Among 23,280 students listed on the 42 intervention school registers, 10,079 (43.3%) aged 5–20 years were enrolled into the IPT intervention and received at least one dose of DP; of these, 9286 (92.1%) received at least one full (3-day) course. In total, 1092 children were enrolled into the final school survey (546 per arm) and had a thick blood smear done; of these, 255 had haemoglobin measured (129 intervention, 126 control). Children in the intervention arm were less likely to have asexual parasites (9.2% intervention vs 44.1% control, adjusted risk ratio [aRR] 0.22 [95% CI 0.16–0.30] p Conclusions School-aged children are a major reservoir of malaria parasites. Delivering IPT to schoolchildren would benefit individual children and may reduce transmission. School-based IPT could help to intensify malaria control toward elimination, and should be considered for policies and programmes. Trial registration Clinicaltrials.gov (NCT02009215), Registered 11 December 2013. https://clinicaltrials.gov/ct2/show/NCT02009215

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

Background Environmental factors play a major role in transmission of malaria given their relationship to both the development and survival of the mosquito and parasite. The associations between environmental factors and malaria can be used to inform the development of early warning systems for increases in malaria burden. The objective of this study was to assess temporal relationships between rainfall, temperature and vegetation with malaria morbidity across three different transmission settings in Uganda. Methods Temporal relationships between environmental factors (weekly total rainfall, mean day time temperature and enhanced vegetation index series) and malaria morbidity (weekly malaria case count data and test positivity rate series) over the period January 2010–May 2013 in three sites located in varying malaria transmission settings in Uganda was explored using cross-correlation with pre-whitening. Sites included Kamwezi (low transmission), Kasambya (moderate transmission) and Nagongera (high transmission). Results Nagongera received the most rain (30.6 mm) and experienced, on average, the highest daytime temperatures (29.8 °C) per week. In the study period, weekly TPR and number of malaria cases were highest at Kasambya and lowest at Kamwezi. The largest cross-correlation coefficients between environmental factors and malaria morbidity for each site was 0.27 for Kamwezi (rainfall and cases), 0.21 for Kasambya (vegetation and TPR), and −0.27 for Nagongera (daytime temperature and TPR). Temporal associations between environmental factors (rainfall, temperature and vegetation) with malaria morbidity (number of malaria cases and TPR) varied by transmission setting. Longer time lags were observed at Kamwezi and Kasambya compared to Nagongera in the relationship between rainfall and number of malaria cases. Comparable time lags were observed at Kasambya and Nagongera in the relationship between temperature and malaria morbidity. Temporal analysis of vegetation with malaria morbidity revealed longer lags at Kasambya compared to those observed at the other two sites. Conclusions This study showed that temporal associations between environmental factors with malaria morbidity vary by transmission setting in Uganda. This suggests the need to incorporate local transmission differences when developing malaria early warning systems that have environmental predictors in Uganda. This will result in development of more accurate early warning systems, which are a prerequisite for effective malaria control in such a setting.

Background An increase in effective malaria control since 2000 has contributed to a decline in global malaria morbidity and mortality. Knowing when and how existing interventions could be combined to maximise their impact on malaria vectors can provide valuable information for national malaria control programs in different malaria endemic settings. Here, we assess the effect of indoor residual spraying on malaria vector densities in a high malaria endemic setting in eastern Uganda as part of a cohort study where the use of long-lasting insecticidal nets (LLINs) was high. Methods Anopheles mosquitoes were sampled monthly using CDC light traps in 107 households selected randomly. Information on the use of malaria interventions in households was also gathered and recorded via a questionnaire. A Bayesian spatio-temporal model was then used to estimate mosquito densities adjusting for climatic and ecological variables and interventions. Results Anopheles gambiae (sensu lato) were most abundant (89.1%; n = 119,008) compared to An. funestus (sensu lato) (10.1%, n = 13,529). Modelling results suggest that the addition of indoor residual spraying (bendiocarb) in an area with high coverage of permethrin-impregnated LLINs (99%) was associated with a major decrease in mosquito vector densities. The impact on An. funestus (s.l.) (Rate Ratio 0.1508; 97.5% CI: 0.0144–0.8495) was twice as great as for An. gambiae (s.l.) (RR 0.5941; 97.5% CI: 0.1432–0.8577). Conclusions High coverage of active ingredients on walls depressed vector populations in intense malaria transmission settings. Sustained use of combined interventions would have a long-term impact on mosquito densities, limiting infectious biting. Electronic supplementary material The online version of this article (doi:10.1186/s13071-016-1917-3) contains supplementary material, which is available to authorized users.

Optimizing quality of care for malaria and other febrile illnesses is a complex challenge of major public health importance. To evaluate the impact of an intervention aiming to improve malaria case management on the health of community children, a cluster-randomized trial was conducted from 2010–2013 in Tororo, Uganda, where malaria transmission is high. Twenty public health centers were included; 10 were randomized in a 1:1 ratio to intervention or control. Households within 2 km of health centers provided the sampling frame for the evaluation. The PRIME intervention included training in fever case management using malaria rapid diagnostic tests (mRDTs), patient-centered services, and health center management; plus provision of mRDTs and artemether–lumefantrine. Cross-sectional community surveys were conducted at baseline and endline (N = 8,766), and a cohort of children was followed for approximately 18 months (N = 992). The primary outcome was prevalence of anemia (hemoglobin < 11.0 g/dL) in children under 5 years of age in the final community survey. The intervention was delivered successfully; however, no differences in prevalence of anemia or parasitemia were observed between the study arms in the final community survey or the cohort. In the final survey, prevalence of anemia in children under 5 years of age was 62.5% in the intervention versus 63.1% in control (adjusted risk ratio = 1.01; 95% confidence interval = 0.91–1.13; P = 0.82). The PRIME intervention, focusing on training and commodities, did not produce the expected health benefits in community children in Tororo. This challenges common assumptions that improving quality of care and access to malaria diagnostics will yield health gains. This work was supported by the ACT Consortium (http://www.actconsortium.org/) through a grant from the Bill & Melinda Gates Foundation to the London School of Hygiene and Tropical Medicine.

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 The 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. Methods The 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. Results Age 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. Conclusions Adjusting 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.