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BackgroundLong-lasting insecticidal nets (LLINs) and indoor residual spraying of insecticide (IRS) are the primary vector control interventions used to prevent malaria in Africa. Although both interventions are effective in some settings, high-quality evidence is rarely available to evaluate their effectiveness following deployment by a national malaria control program. In Uganda, we measured changes in key malaria indicators following universal LLIN distribution in three sites, with the addition of IRS at one of these sites.Methods and findingsComprehensive malaria surveillance was conducted from October 1, 2011, to March 31, 2016, in three sub-counties with relatively low (Walukuba), moderate (Kihihi), and high transmission (Nagongera). Between 2013 and 2014, universal LLIN distribution campaigns were conducted in all sites, and in December 2014, IRS with the carbamate bendiocarb was initiated in Nagongera. High-quality surveillance evaluated malaria metrics and mosquito exposure before and after interventions through (a) enhanced health-facility-based surveillance to estimate malaria test positivity rate (TPR), expressed as the number testing positive for malaria/number tested for malaria (number of children tested for malaria: Walukuba = 42,833, Kihihi = 28,790, and Nagongera = 38,690); (b) cohort studies to estimate the incidence of malaria, expressed as the number of episodes per person-year [PPY] at risk (number of children observed: Walukuba = 340, Kihihi = 380, and Nagongera = 361); and (c) entomology surveys to estimate household-level human biting rate (HBR), expressed as the number of female Anopheles mosquitoes collected per house-night of collection (number of households observed: Walukuba = 117, Kihihi = 107, and Nagongera = 107). The LLIN distribution campaign substantially increased LLIN coverage levels at the three sites to between 65.0% and 95.5% of households with at least one LLIN. In Walukuba, over the 28-mo post-intervention period, universal LLIN distribution was associated with no change in the incidence of malaria (0.39 episodes PPY pre-intervention versus 0.20 post-intervention; adjusted rate ratio [aRR] = 1.02, 95% CI 0.36-2.91, p = 0.97) and non-significant reductions in the TPR (26.5% pre-intervention versus 26.2% post-intervention; aRR = 0.70, 95% CI 0.46-1.06, p = 0.09) and HBR (1.07 mosquitoes per house-night pre-intervention versus 0.71 post-intervention; aRR = 0.41, 95% CI 0.14-1.18, p = 0.10). In Kihihi, over the 21-mo post-intervention period, universal LLIN distribution was associated with a reduction in the incidence of malaria (1.77 pre-intervention versus 1.89 post-intervention; aRR = 0.65, 95% CI 0.43-0.98, p = 0.04) but no significant change in the TPR (49.3% pre-intervention versus 45.9% post-intervention; aRR = 0.83, 95% 0.58-1.18, p = 0.30) or HBR (4.06 pre-intervention versus 2.44 post-intervention; aRR = 0.71, 95% CI 0.30-1.64, p = 0.40). In Nagongera, over the 12-mo post-intervention period, universal LLIN distribution was associated with a reduction in the TPR (45.3% pre-intervention versus 36.5% post-intervention; aRR = 0.82, 95% CI 0.76-0.88, p < 0.001) but no significant change in the incidence of malaria (2.82 pre-intervention versus 3.28 post-intervention; aRR = 1.10, 95% 0.76-1.59, p = 0.60) or HBR (41.04 pre-intervention versus 20.15 post-intervention; aRR = 0.87, 95% CI 0.31-2.47, p = 0.80). The addition of three rounds of IRS at ~6-mo intervals in Nagongera was followed by clear decreases in all outcomes: incidence of malaria (3.25 pre-intervention versus 0.63 post-intervention; aRR = 0.13, 95% CI 0.07-0.27, p < 0.001), TPR (37.8% pre-intervention versus 15.0% post-intervention; aRR = 0.54, 95% CI 0.49-0.60, p < 0.001), and HBR (18.71 pre-intervention versus 3.23 post-intervention; aRR = 0.29, 95% CI 0.17-0.50, p < 0.001). High levels of pyrethroid resistance were documented at all three study sites. Limitations of the study included the observational study design, the lack of contemporaneous control groups, and that the interventions were implemented under programmatic conditions.ConclusionsUniversal distribution of LLINs at three sites with varying transmission intensity was associated with modest declines in the burden of malaria for some indicators, but the addition of IRS at the highest transmission site was associated with a marked decline in the burden of malaria for all indicators. In highly endemic areas of Africa with widespread pyrethroid resistance, IRS using alternative insecticide formulations may be needed to achieve substantial gains in malaria control.

BackgroundMalaria thrives in poor tropical and subtropical countries where local resources are limited. Accurate disease forecasts can provide public and clinical health services with the information needed to implement targeted approaches for malaria control that make effective use of limited resources. The objective of this study was to determine the relevance of environmental and clinical predictors of malaria across different settings in Uganda.MethodsForecasting models were based on health facility data collected by the Uganda Malaria Surveillance Project and satellite-derived rainfall, temperature, and vegetation estimates from 2006 to 2013. Facility-specific forecasting models of confirmed malaria were developed using multivariate autoregressive integrated moving average models and produced weekly forecast horizons over a 52-week forecasting period.ResultsThe model with the most accurate forecasts varied by site and by forecast horizon. Clinical predictors were retained in the models with the highest predictive power for all facility sites. The average error over the 52 forecasting horizons ranged from 26 to 128% whereas the cumulative burden forecast error ranged from 2 to 22%.ConclusionsClinical data, such as drug treatment, could be used to improve the accuracy of malaria predictions in endemic settings when coupled with environmental predictors. Further exploration of malaria forecasting is necessary to improve its accuracy and value in practice, including examining other environmental and intervention predictors, including insecticide-treated nets.

Objective To illustrate the use of a new method for defining the catchment areas of health-care facilities based on their utilization. Methods The catchment areas of six health-care facilities in Uganda were determined using the cumulative case ratio: the ratio of the observed to expected utilization of a facility for a particular condition by patients from small administrative areas. The cumulative case ratio for malaria-related visits to these facilities was determined using data from the Uganda Malaria Surveillance Project. Catchment areas were also derived using various straight line and road network distances from the facility. Subsequently, the 1-year cumulative malaria case rate was calculated for each catchment area, as determined using the three methods. Findings The 1-year cumulative, malaria case rate varied considerably with the method used to define the catchment areas. With the cumulative case ratio approach, the catchment area could include noncontiguous areas. With the distance approaches, the denominator increased substantially with distance, whereas the numerator increased only slightly. The largest cumulative case rate per 1000 population was for the Kamwezi facility: 234.9 (95% confidence interval, CI: 226.2-243.8) for a straight-line distance of 5 km, 193.1 (95% CI: 186.8-199.6) for the cumulative case ratio approach and 156.1 (95% CI: 150.9-161.4) for a road network distance of 5 km. Conclusion Use of the cumulative case ratio for malaria-related visits to determine health-care facility catchment areas was feasible. Moreover, this approach took into account patients'actual addresses, whereas using distance from the facility did not. [TEXT NOT REPRODUCIBLE IN ASCII] Objectif Illustrer l'utilisation d'une nouvelle methode de definition des zones desservies par les etablissements de soins de sante en fonction de leur utilisation par les patients. Methodes Les zones desservies paro etablissements de soins de sante en Ouganda ont ete determinees en utilisant le rapport cumulatif des cas: c'est-a-dire le rapport des utilisations observees sur les utilisations attendues d'un etablissement par les patients provenant de petites zones administratives et consultant pour une maladie particuliere. Le rapport cumulatif de cas pour les consultations liees au paludisme a ete determine a l'aide des donnees du Projet de Surveillance du Paludisme en Ouganda. Les zones desservies ont egalement ete obtenues en utilisant differentes distances en ligne droite et differentes distances de reseau routiera partir de l'etablissement. Ensuite, le taux cumulatif des cas de paludisme a ete calcule pour chaque zone desservie, telle que determinee a l'aide des trois methodes. Resultats Le taux cumulatif des cas de paludisme de la premiere annee variait considerablement en fonction de la methode utilisee pour definir les zones desservies. Avec l'approche des rapports cumulates des cas, la zone desservie pouvalt indure des zones non contigues. Avec les approches des distances, le denominateur augmentait considerablement avec la distance, alors que le numerateur n'augmentait que legerement. Le plus grand taux cumulatif des cas pour 1 000 habitants a ete obtenu pour l'etablissement de Kamwezi: 234,9 (intervalle de confiance a 95%, IC: 226,2-243,8) pour une distance en ligne droite de 5 km, 193,1 (IC a 95%: 186,8-199,6) pour l'approche de rapport cumulatif des cas et 156,1 (IC a 95%: 150,9-161,4) pour une distance de reseau routier de 5 km. Conclusion II est possible d'utillser le rapport cumulatif des cas pour les consultations liees au paludisme afin de determiner les zones desservies par les etablissements de soins de sante. En outre, cette approche prend en compte les adresses reelles des patients, alors que ce n'est pas le cas lorsque l'on utilise les distances a partir des etablissements de soins de sante. [TEXT NOT REPRODUCIBLE IN ASCII] Objetivo Ilustrar el uso de un nuevo metodo para definir las areas de captacion de los centros de salud basado en su uso. Metodos Se determinaron las areas de captacion de seis centros de salud en Uganda mediante el cociente de caso acumulativo: el cociente entre el uso observado y el uso previsto de un centro para una condicion particular por parte de pacientes de pequenas areas administrativas. Se determino el cociente de caso acumulativo de las visitas relacionadas con el paludismo a dichos centros utilizando los datos del Proyecto de vigilancia de la malaria en Uganda. Tambien se obtuvieron las areas de captacion en base a varias distancias lineales y de red vial respecto al centro de salud. Posteriormente, se calculo la tasa acumulativa de casos de malaria de un ano para cada area de captacion, determinada mediante los tres metodos. Resultados La tasa acumulativa de casos de malaria de un ano vario considerablemente con el metodo utilizado para definir las areas de captacion. Mediante el enfoque de la tasa acumulativa de casos, el area de captacion podria incluir areas no contiguas. Con los enfoques basados en la distancia, el denominador aumento sustancialmente con la distancia, mientras que el numerador solo aumento ligeramente. La mayor tasa acumulativa por 1000 habitantes se dio en el centro de Kamwezi: 234,9 (intervalo de confianza del 95 %, 1C: 226,2-243,8) para una distancia lineal de 5 km, 193,1 (1C del 95 %: 186,8-199,6) para el enfoque de la tasa acumulativa de casos y 156,1 (IC del 95%: 150,9-161,4) para una distancia de red vial de 5 km. Conclusion El uso de la tasa acumulativa de casos para las visitas relacionadas con el paludismo a fin de determinar las areas de captacion de centros de salud fue factible. Ademas, este enfoque tuvo en cuenta las direcciones reales de los pacientes, mientras que el enfoque basado en la distancia respecto al centro no las considero., Abstracts in [TEXT NOT REPRODUCIBLE IN ASCII] and Espanol at the end of each article. Introduction Knowledge of a health-care facility's catchment area is important for assessing health service utilization, [...]

Background: Indoor residual spraying (IRS) is widely used as a vector control measure, although there are conflicting findings of its effectiveness in reducing malaria incidence. The objective of this study was to estimate the effect of multiple IRS rounds on malaria incidence and hemoglobin levels in a cohort of children in rural southeastern Uganda.Methods: The study was based upon a dynamic cohort of children aged 0.5-10 years enrolled from August 2011 to June 2017 in Nagongera Subcounty. Confirmed malaria infections and hemoglobin levels were recorded over time for each participant. After each of 4 rounds of IRS, malaria incidence, hemoglobin levels, and parasite density were evaluated and compared with pre-IRS levels. Analyses were carried out at the participant level while accounting for repeated measures and clustering by household.Results: Incidence rate ratios comparing post-IRS to pre-IRS incidence rates for age groups 0-3, 3-5, and 5-11 were 0.108 (95% confidence interval [CI], .078-.149), 0.173 (95% CI, .136-.222), and 0.226 (95% CI, .187-.274), respectively. The mean hemoglobin levels significantly increased from 11.01 (pre-IRS) to 12.18 g/dL (post-IRS).Conclusions: Our study supports the policy recommendation of IRS usage in a stable and perennial transmission area to rapidly reduce malaria transmission. [ABSTRACT FROM AUTHOR]