Indoor residual spraying of insecticide and malaria morbidity in a high transmission intensity area of Uganda.

BackgroundRecently the use of indoor residual spraying of insecticide (IRS) has greatly increased in Africa; however, limited data exist on the quantitative impacts of IRS on health outcomes in highly malaria endemic areas.Methodology/principal findingsRoutine data were collected on more than 90,000 patient visits at a single health facility over a 56 month period covering five rounds of IRS using three different insecticides. Temporal associations between the timing of IRS and the probability of a patient referred for microscopy having laboratory confirmed malaria were estimated controlling for seasonality and age. Considering patients less than five years of age there was a modest decrease in the odds of malaria following the 1(st) round of IRS using DDT (OR = 0.76, p<0.001) and the 2(nd) round using alpha-cypermethrin (OR = 0.83, p = 0.002). Following rounds 3-5 using bendiocarb there was a much greater decrease in the odds of malaria (ORs 0.34, 0.16, 0.17 respectively, p<0.001 for all comparisons). Overall, the impact of IRS was less pronounced among patients 5 years or older.Conclusions/significanceIRS was associated with a reduction in malaria morbidity in an area of high transmission intensity in Uganda and the benefits appeared to be greatest after switching to a carbamate class of insecticide

Anti-malarial prescription practices among outpatients with laboratory-confirmed malaria in the setting of a health facility-based sentinel site surveillance system in Uganda.

BACKGROUND: Most African countries have adopted artemisinin-based combination therapy (ACT) as the first-line treatment for uncomplicated malaria. The World Health Organization now recommends limiting anti-malarial treatment to those with a positive malaria test result. Limited data exist on how these policies have affected ACT prescription practices. METHODS: Data were collected from all outpatients presenting to six public health facilities in Uganda as part of a sentinel site malaria surveillance programme. Training in case management, encouragement of laboratory-based diagnosis of malaria, and regular feedback were provided. Data for this report include patients with laboratory confirmed malaria who were prescribed anti-malarial therapy over a two-year period. Patient visits were analysed in two groups: those considered ACT candidates (defined as uncomplicated malaria with no referral for admission in patients ≥ 4 months of age and ≥ 5 kg in weight) and those who may not have been ACT candidates. Associations between variables of interest and failure to prescribe ACT to patients who were ACT candidates were estimated using multivariable logistic regression. RESULTS: A total of 51,355 patient visits were included in the analysis and 46,265 (90.1%) were classified as ACT candidates. In the ACT candidate group, 94.5% were correctly prescribed ACT. Artemether-lumefantrine made up 97.3% of ACT prescribed. There were significant differences across the sites in the proportion of patients for whom there was a failure to prescribe ACT, ranging from 3.0-9.3%. Young children and woman of childbearing age had higher odds of failure to receive an ACT prescription. Among patients who may not have been ACT candidates, the proportion prescribed quinine versus ACT differed based on if the patient had severe malaria or was referred for admission (93.4% vs 6.5%) or was below age or weight cutoffs for ACT (41.4% vs 57.2%). CONCLUSIONS: High rates of compliance with recommended ACT use can be achieved in resource-limited settings. The unique health facility-based malaria surveillance system operating at these clinical sites may provide a framework for improving appropriate ACT use at other sites in sub-Saharan Africa

Malaria Burden through Routine Reporting: Relationship between Incidence and Test Positivity Rates.

Test positivity rate (TPR)-confirmed cases per 100 suspected cases tested, and test-confirmed malaria case rate (IR)-cases per 1,000 population, are common indicators used routinely for malaria surveillance. However, few studies have explored relationships between these indicators over time and space. We studied the relationship between these indicators in children aged < 11 years presenting with suspected malaria to the outpatient departments of level IV health centers in Nagongera, Kihihi, and Walukuba in Uganda from October 2011 to June 2016. We evaluated trends in indicators over time and space, and explored associations using multivariable regression models. Overall, 65,710 participants visited the three clinics. Pairwise comparisons of TPR and IR by month showed similar trends, particularly for TPRs < 50% and during low-transmission seasons, but by village, the relationship was complex. Village mean annual TPRs remained constant, whereas IRs drastically declined with increasing distance from the health center. Villages that were furthest away from the health centers (fourth quartile for distance) had significantly lower IRs than nearby villages (first quartile), with an incidence rate ratio of 0.40 in Nagongera (95% CI: 0.23-0.63; P = 0.001), 0.55 in Kihihi (0.40-0.75; P < 0.001), and 0.25 in Walukuba (0.12-0.51; P < 0.001). Regression analysis results emphasized a nonlinear (cubic) relationship between TPR and IR, after accounting for month, village, season, and demographic factors. Results show that the two indicators are highly relevant for monitoring malaria burden. However, interpretation differs with TPR primarily indicating demand for malaria treatment resources and IR indicating malaria risk among health facility catchment populations

Anti-malarial prescription practices among children admitted to six public hospitals in Uganda from 2011 to 2013.

BACKGROUND: In 2011, Uganda's Ministry of Health switched policy from presumptive treatment of malaria to recommending parasitological diagnosis prior to treatment, resulting in an expansion of diagnostic services at all levels of public health facilities including hospitals. Despite this change, anti-malarial drugs are often prescribed even when test results are negative. Presented is data on anti-malarial prescription practices among hospitalized children who underwent diagnostic testing after adoption of new treatment guidelines. METHODS: Anti-malarial prescription practices were collected as part of an inpatient malaria surveillance program generating high quality data among children admitted for any reason at government hospitals in six districts. A standardized medical record form was used to collect detailed patient information including presenting symptoms and signs, laboratory test results, admission and final diagnoses, treatments administered, and final outcome upon discharge. RESULTS: Between July 2011 and December 2013, 58,095 children were admitted to the six hospitals (hospital range 3294-20,426).A total of 56,282 (96.9 %) patients were tested for malaria, of which 26,072 (46.3 %) tested positive (hospital range 5.9-57.3 %). Among those testing positive, only 84 (0.3 %) were first tested after admission and 295 of 30,389 (1.0 %) patients who tested negative at admission later tested positive. Of 30,210 children with only negative test results, 11,977 (39.6 %) were prescribed an anti-malarial (hospital range 14.5-53.6 %). The proportion of children with a negative test result who were prescribed an anti-malarial fluctuated over time and did not show a significant trend at any site with the exception of one hospital where a steady decline was observed. Among those with only negative test results, children 6-12 months of age (aOR 3.78; p < 0.001) and those greater than 12 months of age (aOR 4.89; p < 0.001) were more likely to be prescribed an anti-malarial compared to children less than 6 months of age. Children with findings suggestive of severe malaria were also more likely to be prescribed an anti-malarial after a negative test result (aOR 1.98; p < 0.001). CONCLUSIONS: Despite high testing rates for malaria at all sites, prescription of anti-malarials to patients with negative test results remained high, with the exception of one site where a steady decline occurred

Malaria Burden through routine reporting: relationships between incidence estimates

Test positivity rate (TPR)-confirmed cases per 100 suspected cases tested, and test-confirmed malaria case rate (IR)-cases per 1,000 population, are common indicators used routinely for malaria surveillance. However, few studies have explored relationships between these indicators over time and space. We studied the relationship between these indicators in children aged < 11 years presenting with suspected malaria to the outpatient departments of level IV health centers in Nagongera, Kihihi, and Walukuba in Uganda from October 2011 to June 2016. We evaluated trends in indicators over time and space, and explored associations using multivariable regression models. Overall, 65,710 participants visited the three clinics. Pairwise comparisons of TPR and IR by month showed similar trends, particularly for TPRs < 50% and during low-transmission seasons, but by village, the relationship was complex. Village mean annual TPRs remained constant, whereas IRs drastically declined with increasing distance from the health center. Villages that were furthest away from the health centers (fourth quartile for distance) had significantly lower IRs than nearby villages (first quartile), with an incidence rate ratio of 0.40 in Nagongera (95% CI: 0.23-0.63; P = 0.001), 0.55 in Kihihi (0.40-0.75; P < 0.001), and 0.25 in Walukuba (0.12-0.51; P < 0.001). Regression analysis results emphasized a nonlinear (cubic) relationship between TPR and IR, after accounting for month, village, season, and demographic factors. Results show that the two indicators are highly relevant for monitoring malaria burden. However, interpretation differs with TPR primarily indicating demand for malaria treatment resources and IR indicating malaria risk among health facility catchment populations

Comparison of routine health management information system versus enhanced inpatient malaria surveillance for estimating the burden of malaria among children admitted to four hospitals in Uganda.

The primary source of malaria surveillance data in Uganda is the Health Management Information System (HMIS), which does not require laboratory confirmation of reported malaria cases. To improve data quality, an enhanced inpatient malaria surveillance system (EIMSS) was implemented with emphasis on malaria testing of all children admitted in select hospitals. Data were compared between the HMIS and the EIMSS at four hospitals over a period of 12 months. After the implementation of the EIMSS, over 96% of admitted children under 5 years of age underwent laboratory testing for malaria. The HMIS significantly overreported the proportion of children under 5 years of age admitted with malaria (average absolute difference = 19%, range = 8-27% across the four hospitals) compared with the EIMSS. To improve the quality of the HMIS data for malaria surveillance, the National Malaria Control Program should, in addition to increasing malaria testing rates, focus on linking laboratory test results to reported malaria cases

The age-specific incidence of hospitalized paediatric malaria in Uganda.

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

Rapid shifts in the age-specific burden of malaria following successful control interventions in four regions of 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  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  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

Impact of COVID-19 on routine malaria indicators in rural Uganda: an interrupted time series analysis.

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