Bayesian spatio-temporal modelling of malaria surveillance in Uganda

The launch of Roll Back Malaria (RBM) initiative in the early 2000s marked the first serious international efforts to control, prevent and treat malaria in endemic countries of sub-Sahara Africa unparalleled since the demise of the global malaria eradication campaign in the 1960s. These efforts have led to accelerated scale-up of highly proven malaria interventions, that is, insecticide-treated nets, indoor residual spraying, and case management with artemisinin-based combination therapies. This has been followed by a decline of malaria morbidity and mortality in high endemic countries including Uganda which is ranked in the top six high-burden countries. Despite these achievements, malaria remains a major global public health problem and a leading cause of hospitalization and death in Uganda. The RBM support in Uganda has been extended to malaria surveillance specifically to strengthen the national Health Management Information System (HMIS), and periodical implementation of nationally representative household surveys such as Malaria Indicator Survey (MIS) and Demographic Health Surveys (DHS), and facility assessment surveys. The availability of these large datasets notwithstanding, their utilization remains low and the information extracted is limited to national averages that neither take into account subnational heterogeneities and disparities nor evaluate the effects of interventions and other important confounders on malaria burden changes in space and time. In this thesis, we developed Bayesian hierarchical geostatistical and spatio-temporal models for malaria surveillance data collected in Uganda during 2009-2017 to estimate malaria burden, assess interventions and health system-related effects on its changes, and forecast malaria cases to support early warning systems. These models fitted via Markov Chain Monte Carlo (MCMC) simulations offer the flexibility to incorporate correlation of malaria in space and time and can easily be extended to capture complex relationships

Geographical variations of the associations between health interventions and all-cause under-five mortality in Uganda

To reduce the under-five mortality (U5M), fine-gained spatial assessment of the effects of health interventions is critical because national averages can obscure important sub-national disparities. In turn, sub-national estimates can guide control programmes for spatial targeting. The purpose of our study is to quantify associations of interventions with U5M rate at national and sub-national scales in Uganda and to identify interventions associated with the largest reductions in U5M rate at the sub-national scale.; Spatially explicit data on U5M, interventions and sociodemographic indicators were obtained from the 2011 Uganda Demographic and Health Survey (DHS). Climatic data were extracted from remote sensing sources. Bayesian geostatistical Weibull proportional hazards models with spatially varying effects at sub-national scales were utilized to quantify associations between all-cause U5M and interventions at national and regional levels. Bayesian variable selection was employed to select the most important determinants of U5M.; At the national level, interventions associated with the highest reduction in U5M were artemisinin-based combination therapy (hazard rate ratio (HRR) = 0.60; 95% Bayesian credible interval (BCI): 0.11, 0.79), initiation of breastfeeding within 1 h of birth (HR = 0.70; 95% BCI: 0.51, 0.86), intermittent preventive treatment (IPTp) (HRR = 0.74; 95% BCI: 0.67, 0.97) and access to insecticide-treated nets (ITN) (HRR = 0.75; 95% BCI: 0.63, 0.84). In Central 2, Mid-Western and South-West, largest reduction in U5M was associated with access to ITNs. In Mid-North and West-Nile, improved source of drinking water explained most of the U5M reduction. In North-East, improved sanitation facilities were associated with the highest decline in U5M. In Kampala and Mid-Eastern, IPTp had the largest associated with U5M. In Central1 and East-Central, oral rehydration solution and postnatal care were associated with highest decreases in U5M respectively.; Sub-national estimates of the associations between U5M and interventions can guide control programmes for spatial targeting and accelerate progress towards mortality-related Sustainable Development Goals

In-hospital trends of non-communicable disease mortality during the pandemic for patients without COVID-19 at a regional referral hospital in southwestern Uganda

Background Non-communicable diseases (NCDs) represent a growing health burden in sub-Saharan Africa, especially in Uganda. The COVID-19 pandemic presented significant challenges for the Ugandan healthcare system, though changes in hospital admissions and outcomes for adults with NCDs and without COVID-19 infection remain unknown. We evaluated trends of NCD-related in-hospital mortality among patients without COVID-19 in a large regional referral hospital in Uganda from March 2019 through August 2021. Methods Between March 1, 2019, and August 31, 2021, we conducted a chart review of Ugandan adults who carried a history of or were admitted for an NCD to Mbarara Regional Referral Hospital. Based on mortality trends, we broke admissions into three periods: Pre-Pandemic (March 1, 2019, to May 31, 2020), Early Pandemic (June 1, 2020, to March 31, 2021), and Late Pandemic (April 1, 2021, to August 31, 2021), and calculated admission and mortality rates for the most common NCD diagnoses. A multivariable logistic regression model was fitted for a primary outcome of in-hospital mortality. Results Of 3777 total individuals, 1655 were admitted Pre-Pandemic, 1423 in the Early Pandemic, and 699 in the Late Pandemic. We found a five-fold increase in mortality in the Early Pandemic period compared to the Pre-Pandemic and Late Pandemic periods (15.4 vs 2.9 vs 2.4, p < 0.001). Factors associated with increased odds for in-hospital mortality included admission during the Early Pandemic period (odds ratio [OR] 5.59; 95% CI 3.90, 8.02; p < 0.001), admission with hypotension (OR 2.13; 95% CI 1.40, 3.24; p < 0.001), admission diagnosis of malignancy (OR 1.79; 95% CI 1.06, 3.01; p = 0.028) and stroke (OR 1.75; 95% CI 1.06, 2.88; p = 0.028), and each unit increase in SOFA score (OR 1.41; 95% CI 1.30, 1.52; p < 0.001). Length of stay greater than 7 days was associated with decreased odds of in-hospital mortality (OR 0.56; 95%CI 0.40, 0.79; p = 0.001). Conclusions NCD-associated in-hospital mortality was high in the early COVID-19 pandemic period. Disruptions in longitudinal NCD care that occurred due to the pandemic may have been contributory, though this requires further investigation. Future work should focus on NCD care for hospitalized individuals in resource limited settings and developing more resilient systems of NCD care

Measuring health facility readiness and its effects on severe malaria outcomes in Uganda

There is paucity of evidence for the role of health service delivery to the malaria decline in Uganda We developed a methodology to quantify health facility readiness and assessed its role on severe malaria outcomes among lower-level facilities (HCIIIs and HCIIs) in the country. Malaria data was extracted from the Health Management Information System (HMIS). General service and malaria-specific readiness indicators were obtained from the 2013 Uganda service delivery indicator survey. Multiple correspondence analysis (MCA) was used to construct a composite facility readiness score based on multiple factorial axes. Geostatistical models assessed the effect of facility readiness on malaria deaths and severe cases. Malaria readiness was achieved in one-quarter of the facilities. The composite readiness score explained 48% and 46% of the variation in the original indicators compared to 23% and 27%, explained by the first axis alone for HCIIIs and HCIIs, respectively. Mortality rate was 64% (IRR = 0.36, 95% BCI: 0.14-0.61) and 68% (IRR = 0.32, 95% BCI: 0.12-0.54) lower in the medium and high compared to low readiness groups, respectively. A composite readiness index is more informative and consistent than the one based on the first MCA factorial axis. In Uganda, higher facility readiness is associated with a reduced risk of severe malaria outcomes

The effect of case management and vector-control interventions on space-time patterns of malaria incidence in Uganda

Electronic reporting of routine health facility data in Uganda began with the adoption of the District Health Information Software System version 2 (DHIS2) in 2011. This has improved health facility reporting and overall data quality. In this study, the effects of case management with artemisinin-based combination therapy (ACT) and vector control interventions on space-time patterns of disease incidence were determined using DHIS2 data reported during 2013-2016.; Bayesian spatio-temporal negative binomial models were fitted on district-aggregated monthly malaria cases, reported by two age groups, defined by a cut-off age of 5 years. The effects of interventions were adjusted for socio-economic and climatic factors. Spatial and temporal correlations were taken into account by assuming a conditional autoregressive and a first-order autoregressive AR(1) process on district and monthly specific random effects, respectively. Fourier trigonometric functions were incorporated in the models to take into account seasonal fluctuations in malaria transmission.; The temporal variation in incidence was similar in both age groups and depicted a steady decline up to February 2014, followed by an increase from March 2015 onwards. The trends were characterized by a strong bi-annual seasonal pattern with two peaks during May-July and September-December. Average monthly incidence in children < 5 years declined from 74.7 cases (95% CI 72.4-77.1) in 2013 to 49.4 (95% CI 42.9-55.8) per 1000 in 2015 and followed by an increase in 2016 of up to 51.3 (95% CI 42.9-55.8). In individuals ≥ 5 years, a decline in incidence from 2013 to 2015 was followed by an increase in 2016. A 100% increase in insecticide-treated nets (ITN) coverage was associated with a decline in incidence by 44% (95% BCI 28-59%). Similarly, a 100% increase in ACT coverage reduces incidence by 28% (95% BCI 11-45%) and 25% (95% BCI 20-28%) in children < 5 years and individuals ≥ 5 years, respectively. The ITN effect was not statistically important in older individuals. The space-time patterns of malaria incidence in children < 5 are similar to those of parasitaemia risk predicted from the malaria indicator survey of 2014-15.; The decline in malaria incidence highlights the effectiveness of vector-control interventions and case management with ACT in Uganda. This calls for optimizing and sustaining interventions to achieve universal coverage and curb reverses in malaria decline

Implementation of the Malaria Test, Treat and Track Policy in Health Facilities in Gulu District, Uganda: A Cross-Sectional Study

Abstract Background An essential means to control malaria is diagnosing suspected patients with a confirmatory test, treatment of malaria confirmed cases, and proper case registration (track). In 2011, the Ministry of Health launched a country-wide malaria Test, Treat and Track policy. We assessed implementation of the malaria Test, Treat and Track policy in Gulu district, Uganda. Methods This was a cross sectional study conducted in 8 health facilities in Gulu district. We abstracted data from out-patient and laboratory register from January 2019 to December, 2019. We used a chi-square test to assess differences between levels of categorical variables. We considered a p-value of less 0.05 as cut off for statistical significance. We used Bland-Altman correlation analysis to quantify the numerical consistency between the aggregated malaria cases in out-patient registers, laboratory registers, and District Health Information System 2 (DHIS2) records for Gulu district. We used logistic regression to assess factors associated with the proportion of cases suspected, tested, confirmed and treated. Results The proportion of suspected malaria cases that were tested for malaria was 99.8%, and the proportion of confirmed malaria cases that were treated with antimalarials was 99.9%. There was a poor correlation 0.558(95%CI = 0.319–0.797), when the number of malaria cases recorded in out-patient department (OPD) registers were compared with the number of malaria cases reported in DHIS2 and substantial correlation 0.99(95%CI = 0.997-1.000), when malaria cases recorded in laboratory register were compared to malaria cases reported in DHIS2. There was a significant statistical difference in the proportion of confirmed malaria cases treated with antimalarials across different levels of health facilities − 0.015(95%CI=-0.027-0.003) (p &lt; 0.016) and when health facilities were disaggregated by their location, 0.020(95%CI = 0.020 − 0.013) (p &lt; 0.004). Conclusion Substantial compliance was observed in testing and treatment of malaria cases. However, malaria data reported in DHIS2 was not consistent with data recorded in HMIS registers at health facilities. There is a need to conduct capacity-building on malaria data management and integrated supportive supervision, as well as develop standard operating procedures for routine data management activities.</jats:p

Associations and contribution of childhood diseases to fever risk among children less than five years in Uganda

# Background Despite massive investment in diseases responsible for fever among children less than five years in Uganda, the burden of the fever symptom remains high and disproportionately distributed across regions. In Uganda, studies assessing the relationship between fever prevalence and multiple childhood diseases, especially at a local scale are scanty. We analyse the 2016 Demographic and Health Survey (DHS) data to quantify the associations and contribution of childhood diseases to fever prevalence among children less than five years in Uganda at the national and regional level. Findings can lead to the development and implementation of preventive and treatment measures especially at a local scale to minimize fever-related diseases among the under-fives in Uganda. # Methods Bayesian geostatistical logistic regression models with spatially varying coefficients were fitted to determine the associations and contribution of childhood diseases on fever prevalence at the national and regional levels. Region-specific spatially varying coefficients were modeled by a conditional autoregressive distribution. Cluster-specific random effects were introduced into the model to take into account spatial dependence in fever prevalence. Bayesian geostatistical stochastic search variable selection was applied to determine the most important predictors in explaining variation in fever prevalence. The contribution of childhood diseases to fever prevalence was estimated using population attributable fractions. # Results The prevalence of fever was highest in Busoga and Teso regions and lowest in Bunyoro region. At the national level, the population attribution fraction of diarrhoea, acute respiratory infections (ARI) and malaria to the prevalence of fever in the under-five was 38.12 (95% Bayesian credible intervals, BCI=25.15-41.59), 30.99 (95% BCI=9.82-34.26) and 9.50 (95% BCI=2.34-25.15), respectively. The attribution of diarrhoea was common in all regions except Bunyoro, while ARI was more common in Bugisu, Karamoja and West Nile, and malaria was commonest in Bunyoro. In Lango, the attribution of diarrhoea and ARI was similar. # Conclusions Majority of fevers among the under-five are due to diarrhoea, followed by ARI. Hand washing with soap and water/detergent should be strengthened in all regions. Vaccination against ARI should be encouraged, in the regions of Central 2, Bugisu, Teso, Karamoja, Lango, West-Nile and Tooro. The health system should be reinforced to treat diarrhoea and ARI

The effects and contribution of childhood diseases on the geographical distribution of all-cause under-five mortality in Uganda

Introduction: Information on the causes of death among under-five children is key in designing and implementation of appropriate interventions. In Uganda, civil death registration is incomplete which limits the estimation of disease-related mortality burden especially at a local scale. In the absence of routine cause-specific data, we used household surveys to quantify the effects and contribution of main childhood diseases such as malaria, severe or moderate anaemia, severe or moderate malnutrition, diarrhoea and acute respiratory infections (ARIs) on all-cause under-five mortality (U5M) at national and sub-national levels. We related all-cause U5M with risks of childhood diseases after adjusting for geographical disparities in coverages of health interventions, socio-economic, environmental factors and disease co-endemicities. Methods: Data on U5M, disease prevalence, socio-economic and intervention coverage indicators were obtained from the 2011 Demographic and Health Survey, while data on malaria prevalence were extracted from the 2009 Malaria Indicator Survey. Bayesian geostatistical Weibull proportional hazards models with spatially varying disease effects at sub-national scales were fitted to quantify the associations between childhood diseases and the U5M. Spatial correlation between clusters was incorporated via locational random effects while region-specific random effects with conditional autoregressive prior distributions modeled the geographical variation in the effects of childhood diseases. The models addressed geographical misalignment in the locations of the two surveys. The contribution of childhood diseases to under-five mortality was estimated using population attributable fractions. Results: The overall U5M rate was 90 deaths per 1000 live births. Large regional variations in U5M rates were observed, lowest in Kampala at 56 and highest in the North-East at 152 per 1000 live births. National malaria parasitemia prevalence was 42%, with Kampala experiencing the lowest of 5% and the Mid-North the highest of 62%. About 27% of Ugandan children aged 6–59 months were severely or moderately anaemic; lowest in South-West (8%) and highest in East-Central (46%). Overall, 17% of children were either severely or moderately malnourished. The percentage of moderately/severely malnourished children varied by region with Kampala having the lowest (8%) and North-East the highest (45%). Nearly a quarter of the children under-five years were reported to have diarrhoea at national level, and this proportion was highest in East-Central (32%) and Mid-Eastern (33%) and lowest in South-West (14%). Overall, ARIs in the two weeks before the survey was 15%; highest in Mid-North (22%) and lowest in Central 1 (9%). At national level, the U5M was associated with prevalence of malaria (hazard ratio (HR) = 1.74; 95% BCI: 1.42, 2.16), severe or moderate anaemia (HR =1.37; 95% BCI: 1.20, 1.75), severe or moderate malnutrition (HR = 1.49; 95% BCI: 1.25, 1.66) and diarrhoea (HR = 1.61; 95% BCI: 1.31, 2.05). The relationship between malaria and U5M was important in the regions of Central 2, East-Central, Mid-North, North-East and West-Nile. Diarrhoea was associated with under-five deaths in Central 2, East-central, Mid-Eastern and Mid-Western. Moderate/severe malnutrition was associated with U5M in East-Central, Mid-Eastern and North-East. Moderate/severe anaemia was associated with deaths in Central 1, Kampala, Mid-North, Mid-Western, North-East, South-West and West-Nile.At the national level, 97% (PAF = 96.9; 95%BCI: 94.4, 98.0), 91% (PAF = 90.9; 95%BCI: 84.4, 95.3), 89% (PAF = 89.3; 95%BCI: 76.0,93.8) and 93% (PAF = 93.3 95%BCI: 87.7,96.0) of the deaths among children less than five years in Uganda were attributable to malaria, severe/moderate anaemia, severe/moderate malnutrition and diarrhoea respectively. The attribution of malaria was comparable in Central 2, East-Central, Mid-North, North-East and West-Nile while severe/moderate anaemia was more common in all regions except Central 2, East-Central and Mid-Eastern. The attribution of diarrhoea in Central 2, East-Central, Mid-Eastern and Mid-Western was similar. The attribution of severe/moderate malnutrition was common in East-Central, Mid-Eastern and North-East. Conclusion: In Uganda, the contribution and effects of childhood diseases on U5M vary by region. Majority of the under-five deaths are due to malaria, followed by diarrhoea, severe/moderate anaemia and severe/moderate malnutrition. Thus, strengthening disease-specific interventions especially in the affected regions may be an important strategy to accelerate progress towards the reduction of the U5M as per the SDG target by 2030. In particular, Indoor Residual Spraying, iron supplementation, deworming, exclusive breastfeeding, investment in nutrition and education in nutrition practices, oral rehydration therapy or recommended home fluid, improved sanitation facilities should be improved. Keywords: DHS, Under-five mortality, Malaria, Anaemia, Malnutrition, Diarrhoea, Respiratory infections, Population attributable fractions, Bayesian geostatistical inference, Ugand

Associations and contribution of childhood diseases to fever risk among children less than five years in Uganda

Background Despite massive investment in diseases responsible for fever among children less than five years in Uganda, the burden of the fever symptom remains high and disproportionately distributed across regions. In Uganda, studies assessing the relationship between fever prevalence and multiple childhood diseases, especially at a local scale are scanty. We analyse the 2016 Demographic and Health Survey (DHS) data to quantify the associations and contribution of childhood diseases to fever prevalence among children less than five years in Uganda at the national and regional level. Findings can lead to the development and implementation of preventive and treatment measures especially at a local scale to minimize fever-related diseases among the under-fives in Uganda. Methods Bayesian geostatistical logistic regression models with spatially varying coefficients were fitted to determine the associations and contribution of childhood diseases on fever prevalence at the national and regional levels. Region-specific spatially varying coefficients were modeled by a conditional autoregressive distribution. Cluster-specific random effects were introduced into the model to take into account spatial dependence in fever prevalence. Bayesian geostatistical stochastic search variable selection was applied to determine the most important predictors in explaining variation in fever prevalence. The contribution of childhood diseases to fever prevalence was estimated using population attributable fractions. Results The prevalence of fever was highest in Busoga and Teso regions and lowest in Bunyoro region. At the national level, the population attribution fraction of diarrhoea, acute respiratory infections (ARI) and malaria to the prevalence of fever in the under-five was 38.12 (95% Bayesian credible intervals, BCI=25.15-41.59), 30.99 (95% BCI=9.82-34.26) and 9.50 (95% BCI=2.34-25.15), respectively. The attribution of diarrhoea was common in all regions except Bunyoro, while ARI was more common in Bugisu, Karamoja and West Nile, and malaria was commonest in Bunyoro. In Lango, the attribution of diarrhoea and ARI was similar. Conclusions Majority of fevers among the under-five are due to diarrhoea, followed by ARI. Hand washing with soap and water/detergent should be strengthened in all regions. Vaccination against ARI should be encouraged, in the regions of Central 2, Bugisu, Teso, Karamoja, Lango, West-Nile and Tooro. The health system should be reinforced to treat diarrhoea and ARI. </jats:sec