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Case management of malaria in Africa has evolved markedly over the past 20 years and updated cost estimates are needed to guide malaria control policies. We estimated the cost of malaria illness to households and the public health service and assessed the equity of these costs in Uganda. From December 2021 to May 2022, we conducted a costing exercise in eight government-run health centres covering seven sub-regions, collecting health service costs from patient observations, records review and a time-and-motion study. From November 2021 to January 2022, we gathered data on households' cost of illness from randomly selected households for 614 residents with suspected malaria. Societal costs of illness were estimated and combined with secondary data sources to estimate the total economic burden of malaria in Uganda. We used regression analyses and concentration curves to assess the equity of household costs across age, geographic location and socio-economic status. The mean societal economic cost of treating suspected malaria was $15.12 [95% confidence interval (CI): 12.83-17.14] per outpatient and $27.21 (95% CI: 20.43-33.99) per inpatient case. Households incurred 81% of outpatient and 72% of inpatient costs. Households bore nearly equal costs of illness, regardless of socio-economic status. A case of malaria cost households in the lowest quintile 26% of per capita monthly consumption, while a malaria case only cost households in the highest quintile 8%. We estimated the societal cost of malaria treatment in Uganda was $577 million (range: $302 million-1.09 billion) in 2021. The cost of malaria remains high in Uganda. Households bear the major burden of these costs. Poorer and richer households incur the same costs per case; this distribution is equal, but not equitable. These results can be applied to parameterize future economic evaluations of malaria control interventions and to evaluate the impact of malaria on Ugandan society, informing resource allocations in malaria prevention., (© The Author(s) 2024. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.)

Background: Understanding COVID-19's impact on children is vital for public health policy, yet age-specific data is scarce, especially in Uganda. This study examines SARS-CoV-2 seroprevalence and risk factors among Ugandan children at two timepoints, along with COVID-19-related knowledge and practices in households, including adult vaccination status., Methods: Baseline surveys were conducted in 12 communities from April to May 2021 (post-Alpha wave) and follow-up surveys in 32 communities from November 2021 to March 2022 (Omicron wave). Household questionnaires and blood samples were collected to test for malaria by microscopy and for SARS-CoV-2 using a Luminex assay. Seroprevalence was estimated at both the survey and community level. Mixed-effects logistic regression models assessed the association between individual and household factors and SARS-CoV-2 seropositivity in children, adjusting for household clustering., Results: More households reported disruptions in daily life at baseline compared to follow-up, though economic impacts lingered. By the follow-up survey, 52.7% of adults had received at least one COVID-19 vaccine dose. Overall seroprevalence in children was higher at follow-up compared to baseline (71.6% versus 19.2%, p < 0.001). Seroprevalence in children ranged across communities from 6-37% at baseline and 50-90% at follow-up. At baseline, children from the poorest households were more likely to be infected. Increasing age remained the only consistent risk factor for SARS-CoV-2 seroconversion at both timepoints., Conclusions: Results indicate that a larger number of children were infected during the Delta and Omicron waves of COVID-19 compared to the Alpha wave. This study is the largest seroprevalence survey in children in Uganda, providing evidence that most children were infected with SARS-CoV-2 before the vaccine was widely available to pediatric populations. Pediatric infections were vastly underreported by case counts, highlighting the importance of seroprevalence surveys in assessing disease burden when testing and reporting rates are limited and many cases are mild or asymptomatic., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Bagala et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The early detection and management of infections is crucial to control epidemics. We evaluated the feasibility and utility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigen rapid diagnostic tests (Ag-RDTs) for the timely detection of and response to coronavirus disease 2019 in high-risk border communities in Uganda. Between May and September 2022, monthly cross-sectional surveys were conducted in 11 schools and two markets in two border districts. Only baseline and end-line testing were also performed in matched control communities. Antigen rapid diagnostic test results and demographic and clinical data were collected, and contacts of patients were traced and tested. All patients were advised to self-isolate, and compliance was assessed on day 5. We enrolled 10,406 participants out of 10,472 screened individuals. The participants had a 1.3% test positivity rate, with schools recording higher, but non-significant, positivity rates than markets (1.4% versus 0.9%; P = 0.149). We tracked 556 contacts, and 536 (96.4%) agreed to test. The test positivity rate was significantly higher among contacts than the index participants (8.8% versus 1.3%; P <0.001). Only 55 (29.7%) of the index participants self-isolated effectively. Settings that received monthly testing had lower end-line positivity rates than controls (0.3% versus 1.4%; P = 0.001). Repeated SARS-CoV-2 Ag-RDT testing is feasible and could reduce SARS-CoV-2 infections. However, the participation in testing may have been enhanced by the compensation provided. Also, isolation was limited, which may reduce the impact of the intervention when rolled out on a large scale. Innovative strategies to increase the isolation of patients could improve the utility of early testing for transmission reduction during epidemics.

Background: Understanding COVID-19's impact on children is vital for public health policy, yet age-specific data is scarce, especially in Uganda. This study examines SARS-CoV-2 seroprevalence and risk factors among Ugandan children at two timepoints, along with COVID-19-related knowledge and practices in households, including adult vaccination status., Methods: Baseline surveys were conducted in 12 communities from April to May 2021 (post-Alpha wave) and follow-up surveys in 32 communities from November 2021 to March 2022 (Omicron wave). Household questionnaires and blood samples were collected to test for malaria by microscopy and for SARS-CoV-2 using a Luminex assay. Seroprevalence was estimated at both the survey and community level. Mixed-effects logistic regression models assessed the association between individual and household factors and SARS-CoV-2 seropositivity in children, adjusting for household clustering., Results: More households reported disruptions in daily life at baseline compared to follow-up, though economic impacts lingered. By the follow-up survey, 52.7% of adults had received at least one COVID-19 vaccine dose. Overall seroprevalence in children was higher at follow-up compared to baseline (71.6% versus 19.2%, p < 0.001). Seroprevalence in children ranged across communities from 6-37% at baseline and 50-90% at follow-up. At baseline, children from the poorest households were more likely to be infected. Increasing age remained the only consistent risk factor for SARS-CoV-2 seroconversion at both timepoints., Conclusions: Results indicate that a larger number of children were infected by the Delta and Omicron waves of COVID-19 compared to the Alpha wave. This study is the largest seroprevalence survey in children in Uganda, providing evidence that most children were infected with SARS-CoV-2 before the vaccine was widely available to pediatric populations. Pediatric infections were vastly underreported by case counts, highlighting the importance of seroprevalence surveys in assessing disease burden when testing and reporting rates are limited and many cases are mild or asymptomatic., Competing Interests: Competing Interest Declaration The authors have no competing interests.

Background: Well-built housing limits mosquito entry and can reduce malaria transmission. The association between community-level housing and malaria burden in Uganda was assessed using data from randomly selected households near 64 health facilities in 32 districts., Methods: Houses were classified as 'improved' (synthetic walls and roofs, eaves closed or absent) or 'less-improved' (all other construction). Associations between housing and parasitaemia were made using mixed effects logistic regression (individual-level) and multivariable fractional response logistic regression (community-level), and between housing and malaria incidence using multivariable Poisson regression., Results: Between November 2021 and March 2022, 4.893 children aged 2-10 years were enrolled from 3.518 houses; of these, 1.389 (39.5%) were classified as improved. Children living in improved houses had 58% lower odds (adjusted odds ratio = 0.42, 95% CI 0.33-0.53, p < 0.0001) of parasitaemia than children living in less-improved houses. Communities with > 67% of houses improved had a 63% lower parasite prevalence (adjusted prevalence ratio 0.37, 95% CI 0.19-0.70, p < 0.0021) and 60% lower malaria incidence (adjusted incidence rate ratio 0.40, 95% CI 0.36-0.44, p < 0.0001) compared to communities with < 39% of houses improved., Conclusions: Improved housing was strongly associated with lower malaria burden across a range of settings in Uganda and should be utilized for malaria control., (© 2024. The Author(s).)

Background: Disruptions in malaria control due to COVID-19 mitigation measures were predicted to increase malaria morbidity and mortality in Africa substantially. In Uganda, long-lasting insecticidal nets (LLINs) are distributed nationwide every 3-4 years, but the 2020-2021 campaign was altered because of COVID-19 restrictions so that the timing of delivery of new nets was different from the original plans made by the National Malaria Control Programme., Methods: A transmission dynamics modelling exercise was conducted to explore how the altered delivery of LLINs in 2020-2021 impacted malaria burden in Uganda. Data were available on the planned LLIN distribution schedule for 2020-2021, and the actual delivery. The transmission model was used to simulate 100 health sub-districts, and parameterized to match understanding of local mosquito bionomics, net use estimates, and seasonal patterns based on data collected in 2017-2019 during a cluster-randomized trial (LLINEUP). Two scenarios were compared; simulated LLIN distributions matching the actual delivery schedule, and a comparable scenario simulating LLIN distributions as originally planned. Model parameters were otherwise matched between simulations., Results: Approximately 70% of the study population received LLINs later than scheduled in 2020-2021, although some areas received LLINs earlier than planned. The model indicates that malaria incidence in 2020 was substantially higher in areas that received LLINs late. In some areas, early distribution of LLINs appeared less effective than the original distribution schedule, possibly due to attrition of LLINs prior to transmission peaks, and waning LLIN efficacy after distribution. On average, the model simulations predicted broadly similar overall mean malaria incidence in 2021 and 2022. After accounting for differences in cluster population size and LLIN distribution dates, no substantial increase in malaria burden was detected., Conclusions: The model results suggest that the disruptions in the 2020-2021 LLIN distribution campaign in Uganda did not substantially increase malaria burden in the study areas., (© 2024. The Author(s).)

Many studies have projected malaria risks with climate change scenarios by modelling one or two environmental variables and without the consideration of malaria control interventions. We aimed to predict the risk of malaria with climate change considering the influence of rainfall, humidity, temperatures, vegetation, and vector control interventions (indoor residual spraying (IRS) and long-lasting insecticidal nets (LLIN)). We used negative binomial models based on weekly malaria data from six facility-based surveillance sites in Uganda from 2010-2018, to estimate associations between malaria, environmental variables and interventions, accounting for the non-linearity of environmental variables. Associations were applied to future climate scenarios to predict malaria distribution using an ensemble of Regional Climate Models under two Representative Concentration Pathways (RCP4.5 and RCP8.5). Predictions including interaction effects between environmental variables and interventions were also explored. The results showed upward trends in the annual malaria cases by 25% to 30% by 2050s in the absence of intervention but there was great variability in the predictions (historical vs RCP 4.5 medians [Min-Max]: 16,785 [9,902-74,382] vs 21,289 [11,796-70,606]). The combination of IRS and LLIN, IRS alone, and LLIN alone would contribute to reducing the malaria burden by 76%, 63% and 35% respectively. Similar conclusions were drawn from the predictions of the models with and without interactions between environmental factors and interventions, suggesting that the interactions have no added value for the predictions. The results highlight the need for maintaining vector control interventions for malaria prevention and control in the context of climate change given the potential public health and economic implications of increasing malaria in Uganda., (© 2024. The Author(s).)

Background: Few studies have explored how vector control interventions may modify associations between environmental factors and malaria., Methods: We used weekly malaria cases reported from six public health facilities in Uganda. Environmental variables (temperature, rainfall, humidity, and vegetation) were extracted from remote sensing sources. The non-linearity of environmental variables was investigated, and negative binomial regression models were used to explore the influence of indoor residual spraying (IRS) and long-lasting insecticidal nets (LLINs) on associations between environmental factors and malaria incident cases for each site as well as pooled across the facilities, with or without considering the interaction between environmental variables and vector control interventions., Results: An average of 73.3 weekly malaria cases per site (range: 0-597) occurred between 2010 and 2018. From the pooled model, malaria risk related to environmental variables was reduced by about 35% with LLINs and 63% with IRS. Significant interactions were observed between some environmental variables and vector control interventions. There was site-specific variability in the shape of the environment-malaria risk relationship and in the influence of interventions (6 to 72% reduction in cases with LLINs and 43 to 74% with IRS)., Conclusion: The influence of vector control interventions on the malaria-environment relationship need to be considered at a local scale in order to efficiently guide control programs.

Background: Partial resistance of Plasmodium falciparum to the artemisinin component of artemisinin-based combination therapies, the most important malaria drugs, emerged in Southeast Asia and now threatens East Africa. Partial resistance, which manifests as delayed clearance after therapy, is mediated principally by mutations in the kelch protein K13 (PfK13). Limited longitudinal data are available on the emergence and spread of artemisinin resistance in Africa., Methods: We performed annual surveillance among patients who presented with uncomplicated malaria at 10 to 16 sites across Uganda from 2016 through 2022. We sequenced the gene encoding kelch 13 ( pfk13 ) and analyzed relatedness using molecular methods. We assessed malaria metrics longitudinally in eight Ugandan districts from 2014 through 2021., Results: By 2021-2022, the prevalence of parasites with validated or candidate resistance markers reached more than 20% in 11 of the 16 districts where surveillance was conducted. The PfK13 469Y and 675V mutations were seen in far northern Uganda in 2016-2017 and increased and spread thereafter, reaching a combined prevalence of 10 to 54% across much of northern Uganda, with spread to other regions. The 469F mutation reached a prevalence of 38 to 40% in one district in southwestern Uganda in 2021-2022. The 561H mutation, previously described in Rwanda, was first seen in southwestern Uganda in 2021, reaching a prevalence of 23% by 2022. The 441L mutation reached a prevalence of 12 to 23% in three districts in western Uganda in 2022. Genetic analysis indicated local emergence of mutant parasites independent of those in Southeast Asia. The emergence of resistance was observed predominantly in areas where effective malaria control had been discontinued or transmission was unstable., Conclusions: Data from Uganda showed the emergence of partial resistance to artemisinins in multiple geographic locations, with increasing prevalence and regional spread over time. (Funded by the National Institutes of Health.)., (Copyright © 2023 Massachusetts Medical Society.)

Introduction: Maps of malaria risk are important tools for allocating resources and tracking progress. Most maps rely on cross-sectional surveys of parasite prevalence, but health facilities represent an underused and powerful data source. We aimed to model and map malaria incidence using health facility data in Uganda., Methods: Using 24 months (2019-2020) of individual-level outpatient data collected from 74 surveillance health facilities located in 41 districts across Uganda (n=445 648 laboratory-confirmed cases), we estimated monthly malaria incidence for parishes within facility catchment areas (n=310) by estimating care-seeking population denominators. We fit spatio-temporal models to the incidence estimates to predict incidence rates for the rest of Uganda, informed by environmental, sociodemographic and intervention variables. We mapped estimated malaria incidence and its uncertainty at the parish level and compared estimates to other metrics of malaria. To quantify the impact that indoor residual spraying (IRS) may have had, we modelled counterfactual scenarios of malaria incidence in the absence of IRS., Results: Over 4567 parish-months, malaria incidence averaged 705 cases per 1000 person-years. Maps indicated high burden in the north and northeast of Uganda, with lower incidence in the districts receiving IRS. District-level estimates of cases correlated with cases reported by the Ministry of Health (Spearman's r=0.68, p<0.0001), but were considerably higher (40 166 418 cases estimated compared with 27 707 794 cases reported), indicating the potential for underreporting by the routine surveillance system. Modelling of counterfactual scenarios suggest that approximately 6.2 million cases were averted due to IRS across the study period in the 14 districts receiving IRS (estimated population 8 381 223)., Conclusion: Outpatient information routinely collected by health systems can be a valuable source of data for mapping malaria burden. National Malaria Control Programmes may consider investing in robust surveillance systems within public health facilities as a low-cost, high benefit tool to identify vulnerable regions and track the impact of interventions., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: In 2020-2021, long-lasting insecticidal nets (LLINs) were distributed nationwide in Uganda during the COVID-19 pandemic. A cross-sectional survey was conducted in 12 districts to evaluate the impact of the campaign 1-5 months after LLIN distribution., Methods: During April-May 2021, households were randomly selected from target areas (1-7 villages) surrounding 12 government-run health facilities established as Malaria Reference Centres; at least 50 households were enrolled per cluster. Outcomes included household ownership of LLINs distributed through the universal coverage campaign (UCC) (at least one UCC LLIN), adequate coverage of UCC LLINs (at least one UCC LLIN per 2 residents), and use of LLINs (resident slept under a LLIN the previous night). Multivariate logistic regression models were used to identify household- and individual-level factors associated with outcomes, controlling for clustering around health facilities., Results: In total, 634 households, with 3342 residents and 1631 bed-nets, were included. Most households (93.4%) owned at least 1 UCC LLIN, but only 56.8% were adequately covered by UCC LLINs. In an adjusted analysis, the factor most strongly associated with adequate coverage by UCC LLINs was fewer household residents (1-4 vs 7-14; adjusted odds ratio [aOR] 12.96, 95% CI 4.76-35.26, p < 0.001; 5-6 vs 7-14 residents; aOR 2.99, 95% CI 1.21-7.42, p = 0.018). Of the 3166 residents of households that owned at least one UCC LLIN, only 1684 (53.2%) lived in adequately covered households; 89.9% of these used an LLIN the previous night, compared to 1034 (69.8%) of 1482 residents living in inadequately covered households. In an adjusted analysis, restricted to residents of inadequately covered households, LLIN use was higher in children under-five than those aged 5-15 years (aOR 3.04, 95% CI 2.08-4.46, p < 0.001), and higher in household heads than distantly-related residents (aOR 3.94, 95% CI 2.38-6.51, p < 0.001)., Conclusions: Uganda's 2021-21 campaign was successful, despite the COVID-19 pandemic. In future campaigns, strategies should be adopted to ensure high LLIN coverage, particularly for larger households. A better understanding of the drivers of LLIN use within households is needed to guide future interventions, educational messages, and behaviour change communication strategies; school-aged children and distantly-related residents appear vulnerable and could be targeted., (© 2022. The Author(s).)

The Program for Resistance, Immunology, Surveillance, and Modeling of Malaria (PRISM) has been conducting malaria research in Uganda since 2010 to improve the understanding of the disease and measure the impact of population-level control interventions in the country. Here, we will summarize key research findings from a series of studies addressing routine health facility-based surveillance, comprehensive cohort studies, studies of the molecular epidemiology, and transmission of malaria, evaluation of antimalarial drug efficacy, and resistance across the country, and assessments of insecticide resistance. Among our key findings are the following. First, we found that in historically high transmission areas of Uganda, a combination of universal distribution of long-lasting insecticidal-treated nets (LLINs) and sustained indoor residual spraying (IRS) of insecticides lowered the malaria burden greatly, but marked resurgences occurred if IRS was discontinued. Second, submicroscopic infections are common and key drivers of malaria transmission, especially in school-age children (5-15 years). Third, markers of drug resistance have changed over time, with new concerning emergence of markers predicting resistance to artemisinin antimalarials. Fourth, insecticide resistance monitoring has demonstrated high levels of resistance to pyrethroids, appreciable impact of the synergist piperonyl butoxide to pyrethroid susceptibility, emerging resistance to carbamates, and complete susceptibility of malaria vectors to organophosphates, which could have important implications for vector control interventions. Overall, PRISM has yielded a wealth of information informing researchers and policy-makers on the malaria burden and opportunities for improved malaria control and eventual elimination in Uganda. Continued studies concerning all the types of surveillance discussed above are ongoing.

Malaria is the leading cause of disease burden in sub-Saharan Africa. In 2010, the East Africa International Center of Excellence for Malaria Research, also known as the Program for Resistance, Immunology, Surveillance, and Modeling of Malaria (PRISM), was established to provide a comprehensive approach to malaria surveillance in Uganda. We instituted cohort studies and a robust malaria and entomological surveillance network at selected public health facilities that have provided a platform for monitoring trends in malaria morbidity and mortality, tracking the impact of malaria control interventions (indoor residual spraying of insecticide [IRS], use of long-lasting insecticidal nets [LLINs], and case management with artemisinin-based combination therapies [ACTs]), as well as monitoring of antimalarial drug and insecticide resistance. PRISM studies have informed Uganda's malaria treatment policies, guided selection of LLINs for national distribution campaigns, and revealed widespread pyrethroid resistance, which led to changes in insecticides delivered through IRS. Our continuous engagement and interaction with policy makers at the Ugandan Ministry of Health have enabled PRISM to share evidence, best practices, and lessons learned with key malaria stakeholders, participate in malaria control program reviews, and contribute to malaria policy and national guidelines. Here, we present an overview of interactions between PRISM team members and Ugandan policy makers to demonstrate how PRISM's research has influenced malaria policy and control in Uganda.

Five years of sustained indoor residual spraying (IRS) of insecticide from 2014 to 2019, first using a carbamate followed by an organophosphate, was associated with a marked reduction in the incidence of malaria in five districts of Uganda. We assessed changes in malaria incidence over an additional 21 months, corresponding to a change in IRS formulations using clothianidin with and without deltamethrin. Using enhanced health facility surveillance data, our objectives were to 1) estimate the impact of IRS on monthly malaria case counts at five surveillance sites over a 6.75 year period, and 2) compare monthly case counts at five facilities receiving IRS to ten facilities in neighboring districts not receiving IRS. For both objectives, we specified mixed effects negative binomial regression models with random intercepts for surveillance site adjusting for rainfall, season, care-seeking, and malaria diagnostic. Following the implementation of IRS, cases were 84% lower in years 4-5 (adjusted incidence rate ratio [aIRR] = 0.16, 95% CI 0.12-0.22), 43% lower in year 6 (aIRR = 0.57, 95% CI 0.44-0.74), and 39% higher in the first 9 months of year 7 (aIRR = 1.39, 95% CI 0.97-1.97) compared to pre-IRS levels. Cases were 67% lower in IRS sites than non-IRS sites in year 6 (aIRR = 0.33, 95% CI 0.17-0.63) but 38% higher in the first 9 months of year 7 (aIRR = 1.38, 95% CI 0.90-2.11). We observed a resurgence in malaria to pre-IRS levels despite sustained IRS. The timing of this resurgence corresponded to a change of active ingredient. Further research is needed to determine causality., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2022 Epstein et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Understanding the age patterns of disease is necessary to target interventions to maximise cost-effective impact. New malaria chemoprevention and vaccine initiatives target young children attending routine immunisation services. Here we explore the relationships between age and severity of malaria hospitalisation versus malaria transmission intensity., Methods: Clinical data from 21 surveillance hospitals in East Africa were reviewed. Malaria admissions aged 1 month to 14 years from discrete administrative areas since 2006 were identified. Each site-time period was matched to a model estimated community-based age-corrected parasite prevalence to provide predictions of prevalence in childhood (PfPR 2-10 ). Admission with all-cause malaria, severe malaria anaemia (SMA), respiratory distress (RD) and cerebral malaria (CM) were analysed as means and predicted probabilities from Bayesian generalised mixed models., Results: 52,684 malaria admissions aged 1 month to 14 years were described at 21 hospitals from 49 site-time locations where PfPR 2-10 varied from < 1 to 48.7%. Twelve site-time periods were described as low transmission (PfPR 2-10 < 5%), five low-moderate transmission (PfPR 2-10 5-9%), 20 moderate transmission (PfPR 2-10 10-29%) and 12 high transmission (PfPR 2-10 ≥ 30%). The majority of malaria admissions were below 5 years of age (69-85%) and rare among children aged 10-14 years (0.7-5.4%) across all transmission settings. The mean age of all-cause malaria hospitalisation was 49.5 months (95% CI 45.1, 55.4) under low transmission compared with 34.1 months (95% CI 30.4, 38.3) at high transmission, with similar trends for each severe malaria phenotype. CM presented among older children at a mean of 48.7 months compared with 39.0 months and 33.7 months for SMA and RD, respectively. In moderate and high transmission settings, 34% and 42% of the children were aged between 2 and 23 months and so within the age range targeted by chemoprevention or vaccines., Conclusions: Targeting chemoprevention or vaccination programmes to areas where community-based parasite prevalence is ≥10% is likely to match the age ranges covered by interventions (e.g. intermittent presumptive treatment in infancy to children aged 2-23 months and current vaccine age eligibility and duration of efficacy) and the age ranges of highest disease burden., (© 2022. The Author(s).)

Background: Routine malaria surveillance data in Africa primarily come from public health facilities reporting to national health management information systems. Although information on gender is routinely collected from patients presenting to these health facilities, stratification of malaria surveillance data by gender is rarely done. This study evaluated gender difference among patients diagnosed with parasitological confirmed malaria at public health facilities in Uganda., Methods: This study utilized individual level patient data collected from January 2020 through April 2021 at 12 public health facilities in Uganda and cross-sectional surveys conducted in target areas around these facilities in April 2021. Associations between gender and the incidence of malaria and non-malarial visits captured at the health facilities from patients residing within the target areas were estimated using poisson regression models controlling for seasonality. Associations between gender and data on health-seeking behaviour from the cross-sectional surveys were estimated using poisson regression models controlling for seasonality., Results: Overall, incidence of malaria diagnosed per 1000 person years was 735 among females and 449 among males (IRR = 1.72, 95% CI 1.68-1.77, p < 0.001), with larger differences among those 15-39 years (IRR = 2.46, 95% CI 2.34-2.58, p < 0.001) and over 39 years (IRR = 2.26, 95% CI 2.05-2.50, p < 0.001) compared to those under 15 years (IRR = 1.46, 95% CI 1.41-1.50, p < 0.001). Female gender was also associated with a higher incidence of visits where malaria was not suspected (IRR = 1.77, 95% CI 1.71-1.83, p < 0.001), with a similar pattern across age strata. These associations were consistent across the 12 individual health centres. From the cross-sectional surveys, females were more likely than males to report fever in the past 2 weeks and seek care at the local health centre (7.5% vs. 4.7%, p = 0.001) with these associations significant for those 15-39 years (RR = 2.49, 95% CI 1.17-5.31, p = 0.018) and over 39 years (RR = 2.56, 95% CI 1.00-6.54, p = 0.049)., Conclusions: Females disproportionately contribute to the burden of malaria diagnosed at public health facilities in Uganda, especially once they reach childbearing age. Contributing factors included more frequent visits to these facilities independent of malaria and a higher reported risk of seeking care at these facilities for febrile illnesses., (© 2022. The Author(s).)

Background: In Uganda, artemether-lumefantrine (AL) is first-line therapy and dihydroartemisinin-piperaquine (DP) second-line therapy for the treatment of uncomplicated malaria. This study evaluated the efficacy and safety of AL and DP in the management of uncomplicated falciparum malaria and measured the prevalence of molecular markers of resistance in three sentinel sites in Uganda from 2018 to 2019., Methods: This was a randomized, open-label, phase IV clinical trial. Children aged 6 months to 10 years with uncomplicated falciparum malaria were randomly assigned to treatment with AL or DP and followed for 28 and 42 days, respectively. Genotyping was used to distinguish recrudescence from new infection, and a Bayesian algorithm was used to assign each treatment failure a posterior probability of recrudescence. For monitoring resistance, Pfk13 and Pfmdr1 genes were Sanger sequenced and plasmepsin-2 copy number was assessed by qPCR., Results: There were no early treatment failures. The uncorrected 28-day cumulative efficacy of AL ranged from 41.2 to 71.2% and the PCR-corrected cumulative 28-day efficacy of AL ranged from 87.2 to 94.4%. The uncorrected 28-day cumulative efficacy of DP ranged from 95.8 to 97.9% and the PCR-corrected cumulative 28-day efficacy of DP ranged from 98.9 to 100%. The uncorrected 42-day efficacy of DP ranged from 73.5 to 87.4% and the PCR-corrected 42-day efficacy of DP ranged from 92.1 to 97.5%. There were no reported serious adverse events associated with any of the regimens. No resistance-associated mutations in the Pfk13 gene were found in the successfully sequenced samples. In the AL arm, the NFD haplotype (N86Y, Y184F, D1246Y) was the predominant Pfmdr1 haplotype, present in 78 of 127 (61%) and 76 of 110 (69%) of the day 0 and day of failure samples, respectively. All the day 0 samples in the DP arm had one copy of the plasmepsin-2 gene., Conclusions: DP remains highly effective and safe for the treatment of uncomplicated malaria in Uganda. Recurrent infections with AL were common. In Busia and Arua, the 95% confidence interval for PCR-corrected AL efficacy fell below 90%. Further efficacy monitoring for AL, including pharmacokinetic studies, is recommended. Trial registration The trail was also registered with the ISRCTN registry with study Trial No. PACTR201811640750761., (© 2021. The Author(s).)

Background: In March 2020, the government of Uganda implemented a strict lockdown policy in response to the COVID-19 pandemic. Interrupted time series analysis (ITSA) was performed to assess whether major changes in outpatient attendance, malaria burden, and case management occurred after the onset of the COVID-19 epidemic in rural Uganda., Methods: Individual level data from all outpatient visits collected from April 2017 to March 2021 at 17 facilities were analysed. Outcomes included total outpatient visits, malaria cases, non-malarial visits, proportion of patients with suspected malaria, proportion of patients tested using rapid diagnostic tests (RDTs), and proportion of malaria cases prescribed artemether-lumefantrine (AL). Poisson regression with generalized estimating equations and fractional regression was used to model count and proportion outcomes, respectively. Pre-COVID trends (April 2017-March 2020) were used to predict the'expected' trend in the absence of COVID-19 introduction. Effects of COVID-19 were estimated over two six-month COVID-19 time periods (April 2020-September 2020 and October 2020-March 2021) by dividing observed values by expected values, and expressed as ratios., Results: A total of 1,442,737 outpatient visits were recorded. Malaria was suspected in 55.3% of visits and 98.8% of these had a malaria diagnostic test performed. ITSA showed no differences between observed and expected total outpatient visits, malaria cases, non-malarial visits, or proportion of visits with suspected malaria after COVID-19 onset. However, in the second six months of the COVID-19 time period, there was a smaller mean proportion of patients tested with RDTs compared to expected (relative prevalence ratio (RPR) = 0.87, CI (0.78-0.97)) and a smaller mean proportion of malaria cases prescribed AL (RPR = 0.94, CI (0.90-0.99))., Conclusions: In the first year after the COVID-19 pandemic arrived in Uganda, there were no major effects on malaria disease burden and indicators of case management at these 17 rural health facilities, except for a modest decrease in the proportion of RDTs used for malaria diagnosis and the mean proportion of malaria cases prescribed AL in the second half of the COVID-19 pandemic year. Continued surveillance will be essential to monitor for changes in trends in malaria indicators so that Uganda can quickly and flexibly respond to challenges imposed by COVID-19., (© 2021. The Author(s).)

Background: Environmental factors such as temperature, rainfall, and vegetation cover play a critical role in malaria transmission. However, quantifying the relationships between environmental factors and measures of disease burden relevant for public health can be complex as effects are often non-linear and subject to temporal lags between when changes in environmental factors lead to changes in malaria incidence. The study investigated the effect of environmental covariates on malaria incidence in high transmission settings of Uganda., Methods: This study leveraged data from seven malaria reference centres (MRCs) located in high transmission settings of Uganda over a 24-month period. Estimates of monthly malaria incidence (MI) were derived from MRCs' catchment areas. Environmental data including monthly temperature, rainfall, and normalized difference vegetation index (NDVI) were obtained from remote sensing sources. A distributed lag nonlinear model was used to investigate the effect of environmental covariates on malaria incidence., Results: Overall, the median (range) monthly temperature was 30 °C (26-47), rainfall 133.0 mm (3.0-247), NDVI 0.66 (0.24-0.80) and MI was 790 per 1000 person-years (73-3973). Temperature of 35 °C was significantly associated with malaria incidence compared to the median observed temperature (30 °C) at month lag 2 (IRR: 2.00, 95% CI: 1.42-2.83) and the increased cumulative IRR of malaria at month lags 1-4, with the highest cumulative IRR of 8.16 (95% CI: 3.41-20.26) at lag-month 4. Rainfall of 200 mm significantly increased IRR of malaria compared to the median observed rainfall (133 mm) at lag-month 0 (IRR: 1.24, 95% CI: 1.01-1.52) and the increased cumulative IRR of malaria at month lags 1-4, with the highest cumulative IRR of 1.99(95% CI: 1.22-2.27) at lag-month 4. Average NVDI of 0.72 significantly increased the cumulative IRR of malaria compared to the median observed NDVI (0.66) at month lags 2-4, with the highest cumulative IRR of 1.57(95% CI: 1.09-2.25) at lag-month 4., Conclusions: In high-malaria transmission settings, high values of environmental covariates were associated with increased cumulative IRR of malaria, with IRR peaks at variable lag times. The complex associations identified are valuable for designing strategies for early warning, prevention, and control of seasonal malaria surges and epidemics., (© 2021. The Author(s).)

Background In March 2020, the government of Uganda implemented a strict lockdown policy in response to the COVID-19 pandemic. We performed an interrupted time series analysis (ITSA) to assess whether major changes in healthcare seeking behavior, malaria burden, and case management occurred after the onset of the COVID-19 epidemic. Methods Individual level data from all outpatient visits occurring from April 2017 through March 2021 at 17 facilities were analyzed. Outcomes included total outpatient visits, malaria cases, non-malarial visits, proportion of visits with suspected malaria, proportion of patients tested using rapid diagnostic tests (RDTs), and proportion of malaria cases prescribed artemether-lumefantrine (AL). Pre-COVID trends measured over a three-year period were extrapolated into the post-COVID period (April 2020- March 2021) using Poisson regression with generalized estimating equations or fractional regression. Effects of COVID-19 were estimated over the 12-month post-COVID period by dividing observed values by the predicted values and expressed as ratios. Results A total of 1,442,737 outpatient visits were recorded. Malaria was suspected in 55.3% of visits and 98.8% of these had a malaria diagnostic test performed. ITSA showed no differences in the observed versus predicted total outpatient visits, malaria cases, non-malarial visits, or proportion of visits with suspected malaria. However, in the second six months of the post-COVID period, there was a smaller mean proportion of patients tested with RDTs compared to predicted (Relative Prevalence Ratio (RPR) = 0.87, CI [0.78, 0.97]) and a smaller mean proportion of malaria cases prescribed AL (RPR = 0.94, CI [0.90, 0.99]. Conclusions There was evidence for a modest decrease in the proportion of RDTs used for malaria diagnosis and the proportion of patients prescribed AL in the second half of the post-COVID year, while other malaria indicators remained stable. Continued surveillance will be essential to monitor for changes in trends in malaria indicators so that Uganda can quickly and flexibly respond to challenges imposed by COVID-19.

The scale-up of malaria control efforts has led to marked reductions in malaria burden over the past twenty years, but progress has slowed. Implementation of indoor residual spraying (IRS) of insecticide, a proven vector control intervention, has been limited and difficult to sustain partly because questions remain on its added impact over widely accepted interventions such as bed nets. Using data from 14 enhanced surveillance health facilities in Uganda, a country with high bed net coverage yet high malaria burden, we estimate the impact of starting and stopping IRS on changes in malaria incidence. We show that stopping IRS was associated with a 5-fold increase in malaria incidence within 10 months, but reinstating IRS was associated with an over 5-fold decrease within 8 months. In areas where IRS was initiated and sustained, malaria incidence dropped by 85% after year 4. IRS could play a critical role in achieving global malaria targets, particularly in areas where progress has stalled.

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 R 2 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 R 2 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: Accurate measures of malaria incidence are essential to track progress and target high-risk populations. While health management information system (HMIS) data provide counts of malaria cases, quantifying the denominator for incidence using these data is challenging because catchment areas and care-seeking behaviours are not well defined. This study's aim was to estimate malaria incidence using HMIS data by adjusting the population denominator accounting for travel time to the health facility., Methods: Outpatient data from two public health facilities in Uganda (Kihihi and Nagongera) over a 3-year period (2011-2014) were used to model the relationship between travel time from patient village of residence (available for each individual) to the facility and the relative probability of attendance using Poisson generalized additive models. Outputs from the model were used to generate a weighted population denominator for each health facility and estimate malaria incidence. Among children aged 6 months to 11 years, monthly HMIS-derived incidence estimates, with and without population denominators weighted by probability of attendance, were compared with gold standard measures of malaria incidence measured in prospective cohorts., Results: A total of 48,898 outpatient visits were recorded across the two sites over the study period. HMIS incidence correlated with cohort incidence over time at both study sites (correlation in Kihihi = 0.64, p < 0.001; correlation in Nagongera = 0.34, p = 0.045). HMIS incidence measures with denominators unweighted by probability of attendance underestimated cohort incidence aggregated over the 3 years in Kihihi (0.5 cases per person-year (PPY) vs 1.7 cases PPY) and Nagongera (0.3 cases PPY vs 3.0 cases PPY). HMIS incidence measures with denominators weighted by probability of attendance were closer to cohort incidence, but remained underestimates (1.1 cases PPY in Kihihi and 1.4 cases PPY in Nagongera)., Conclusions: Although malaria incidence measured using HMIS underestimated incidence measured in cohorts, even when adjusting for probability of attendance, HMIS surveillance data are a promising and scalable source for tracking relative changes in malaria incidence over time, particularly when the population denominator can be estimated by incorporating information on village of residence.

Background: Understanding the relationship between malaria infection risk and disease outcomes represents a fundamental component of morbidity and mortality burden estimations. Contemporary data on severe malaria risks among populations of different parasite exposures are scarce. Using surveillance data, we compared rates of paediatric malaria hospitalisation in areas of varying parasite exposure levels., Methods: Surveillance data at five public hospitals; Jinja, Mubende, Kabale, Tororo, and Apac were assembled among admissions aged 1 month to 14 years between 2017 and 2018. The address of each admission was used to define a local catchment population where national census data was used to define person-year-exposure to risk. Within each catchment, historical infection prevalence was assembled from previously published data and current infection prevalence defined using 33 population-based school surveys among 3400 children. Poisson regression was used to compute the overall and site-specific incidences with 95% confidence intervals., Results: Both current and historical Plasmodium falciparum prevalence varied across the five sites. Current prevalence ranged from < 1% in Kabale to 54% in Apac. Overall, the malaria admission incidence rate (IR) was 7.3 per 1000 person years among children aged 1 month to 14 years of age (95% CI: 7.0, 7.7). The lowest rate was described at Kabale (IR = 0.3; 95 CI: 0.1, 0.6) and highest at Apac (IR = 20.3; 95 CI: 18.9, 21.8). There was a correlation between IR across the five sites and the current parasite prevalence in school children, though findings were not statistically significant. Across all sites, except Kabale, malaria admissions were concentrated among young children, 74% were under 5 years. The median age of malaria admissions at Kabale hospital was 40 months (IQR 20, 72), and at Apac hospital was 36 months (IQR 18, 69). Overall, severe anaemia (7.6%) was the most common presentation and unconsciousness (1.8%) the least common., Conclusion: Malaria hospitalisation rates remain high in Uganda particularly among young children. The incidence of hospitalized malaria in different locations in Uganda appears to be influenced by past parasite exposure, immune acquisition, and current risks of infection. Interruption of transmission through vector control could influence age-specific severe malaria risk.

Global health security depends on effective surveillance for infectious diseases. In Uganda, resources are inadequate to support collection and reporting of data necessary for an effective and responsive surveillance system. We used a cross-cutting approach to improve surveillance and laboratory capacity in Uganda by leveraging an existing pediatric inpatient malaria sentinel surveillance system to collect data on expanded causes of illness, facilitate development of real-time surveillance, and provide data on antimicrobial resistance. Capacity for blood culture collection was established, along with options for serologic testing for select zoonotic conditions, including arboviral infection, brucellosis, and leptospirosis. Detailed demographic, clinical, and laboratory data for all admissions were captured through a web-based system accessible at participating hospitals, laboratories, and the Uganda Public Health Emergency Operations Center. Between July 2016 and December 2017, the expanded system was activated in pediatric wards of 6 regional government hospitals. During that time, patient data were collected from 30,500 pediatric admissions, half of whom were febrile but lacked evidence of malaria. More than 5,000 blood cultures were performed; 4% yielded bacterial pathogens, and another 4% yielded likely contaminants. Several WHO antimicrobial resistance priority pathogens were identified, some with multidrug-resistant phenotypes, including Acinetobacter spp., Citrobacter spp., Escherichia coli, Staphylococcus aureus, and typhoidal and nontyphoidal Salmonella spp. Leptospirosis and arboviral infections (alphaviruses and flaviviruses) were documented. The lessons learned and early results from the development of this multisectoral surveillance system provide the knowledge, infrastructure, and workforce capacity to serve as a foundation to enhance the capacity to detect, report, and rapidly respond to wide-ranging public health concerns in Uganda.