Background Tuberculosis (TB) patients in Uganda incur large costs related to the illness, and while seeking and receiving health care. Such costs create access and adherence barriers which affect health outcomes and increase transmission of disease. The study ascertained the proportion of Ugandan TB affected households incurring catastrophic costs and the main cost drivers. Methods A cross-sectional survey with retrospective data collection and projections was conducted in 2017. A total of 1178 drug resistant (DR) TB (44) and drug sensitive (DS) TB patients (1134), 2 weeks into intensive or continuation phase of treatment were consecutively enrolled across 67 randomly selected TB treatment facilities. Results Of the 1178 respondents, 62.7% were male, 44.7% were aged 15–34 years and 55.5% were HIV positive. For each TB episode, patients on average incurred costs of USD 396 for a DS-TB episode and USD 3722 for a Multi drug resistant tuberculosis (MDR TB) episode. Up to 48.5% of households borrowed, used savings or sold assets to defray these costs. More than half (53.1%) of TB affected households experienced TB-related costs above 20% of their annual household expenditure, with the main cost drivers being non-medical expenditure such as travel, nutritional supplements and food. Conclusion Despite free health care in public health facilities, over half of Ugandan TB affected households experience catastrophic costs. Roll out of social protection interventions like TB assistance programs, insurance schemes, and enforcement of legislation related to social protection through multi-sectoral action plans with central NTP involvement would palliate these costs.

BackgroundWe evaluated the effects and financial costs of two interventions with respect to utilisation of institutional deliveries and other maternal health services in Oyam District in Uganda.MethodsWe conducted a quasi-experimental study involving intervention and comparable/control sub-counties in Oyam District for 12 months (January–December 2014). Participants were women receiving antenatal care, delivery and postnatal care services. We evaluated two interventions: the provision of (1) transport vouchers to women receiving antenatal care and delivering at two health centres (level II) in Acaba sub-county, and (2) baby kits to women who delivered at Ngai Health Centre (level III) in Ngai sub-county. The study outcomes included service coverage of institutional deliveries, four antenatal care visits, postnatal care, and the percentage of women ‘bypassing’ maternal health services inside their resident sub-counties. We calculated the effect of each intervention on study outcomes using the difference in differences analysis. We calculated the cost per institutional delivery and the cost per unit increment in institutional deliveries for each intervention.ResultsOverall, transport vouchers had greater effects on all four outcomes, whereas baby kits mainly influenced institutional deliveries. The absolute increase in institutional deliveries attributable to vouchers was 42.9%; the equivalent for baby kits was 30.0%. Additionally, transport vouchers increased the coverage of four antenatal care visits and postnatal care service coverage by 60.0% and 49.2%, respectively. ‘Bypassing’ was mainly related to transport vouchers and ranged from 7.2% for postnatal care to 11.9% for deliveries. The financial cost of institutional delivery was US$9.4 per transport voucher provided, and US$10.5 per baby kit. The incremental cost per unit increment in institutional deliveries in the transport-voucher system was US$15.9; the equivalent for the baby kit was US$30.6.ConclusionThe transport voucher scheme effectively increased utilisation of maternal health services whereas the baby-kit scheme was only effective in increasing institutional deliveries. The transport vouchers were less costly than the baby kits in the promotion of institutional deliveries. Such incentives can be sustainable if the Ministry of Health integrates them in the health system.Electronic supplementary materialThe online version of this article (10.1186/s12884-017-1623-y) contains supplementary material, which is available to authorized users.

Introduction Despite the limited evidence for its effectiveness, thermal screening at points of entry has increasingly become a standard protocol in numerous parts of the globe in response to the COVID-19 pandemic. We sought to determine the effectiveness of thermal screening as a key step in diagnosing COVID-19 in a resource-limited setting. Materials and methods This was a retrospective cross-sectional study based on a review of body temperature and Xpert Xpress SARS CoV-2 test results records for truck drivers entering Uganda through Mutukula between 15th May and 30th July 2020. All records missing information for body temperature, age, gender, and Xpert Xpress SARS CoV-2 status were excluded from the data set. A data set of 7,181 entries was used to compare thermal screening and Xpert Xpress SARS CoV-2 assay test results using the diagnostic statistical test in STATAv15 software. The prevalence of COVID-19 amongst the truck drivers based on Xpert Xpress SARS CoV-2 assay results was determined. The sensitivity, specificity, positive predictive value, negative predictive value, positive and negative Likelihood ratios were obtained using Xpert Xpress SARS CoV-2 assay as the gold standard. Results Based on our gold standard test, the proportion of persons that tested positive for COVID-19 was 6.7% (95% CI: 6.1–7.3). Of the 7,181 persons that were thermally screened, 6,844 (95.3%) were male. The sample median age was 38 years (interquartile range, IQR: 31–45 years). The median body temperature was 36.5°C (IQR: 36.3–36.7) and only n (1.2%) had a body temperature above 37.5°C. The sensitivity and specificity of thermal screening were 9.9% (95% CI: 7.4–13.0) and 99.5% (95% CI: 99.3–99.6) respectively. The positive and negative predictive values were 57.8 (95% CI: 46.5–68.6) and 93.9 (95% CI: 93.3–94.4) respectively. The positive and negative Likelihood Ratios (LRs) were 19 (95% CI: 12.4–29.1) and 0.9 (95% CI: 0.88–0.93) respectively. Conclusion In this study population, the use of Thermal screening alone is ineffective in the detection of potential COVID-19 cases at point of entry. We recommend a combination of screening tests or additional testing using highly sensitive molecular diagnostics such as Polymerase Chain Reaction.

BackgroundOn 12 October, 2016 a measles outbreak was reported in Mayuge District, eastern Uganda. We investigated the outbreak to determine its scope, identify risk factors for transmission, evaluate vaccination coverage and vaccine effectiveness, and recommend evidence-based control measures.MethodsWe defined a probable case as onset of fever (≥3 days) and generalized rash, plus ≥1 of the following: conjunctivitis, cough, and/or runny nose in a Mayuge District resident. A confirmed case was a probable case with measles-specific IgM (+) not explained by vaccination. We reviewed medical records and conducted active community case-finding. In a case-control investigation involving probable case-persons and controls matched by age and village, we evaluated risk factors for transmission for both cases and controls during the case-person’s likely exposure period (i.e., 7–21 days prior to rash onset). We estimated vaccine effectiveness (VE) using the formula: VE ≈ (1-ORprotective) × 100. We calculated vaccination coverage using the percentage of controls vaccinated.ResultsWe identified 62 probable case-persons (attack rate [AR] = 4.0/10,000), including 3 confirmed. Of all age groups, children < 5 years were the most affected (AR = 14/10,000). The epidemic curve showed a propagated outbreak. Thirty-two percent (13/41) of case-persons and 13% (21/161) of control-persons visited water-collection sites (by themselves or with parents) during the case-persons’ likely exposure period (ORM-H = 5.0; 95% CI = 1.5–17). Among children aged 9–59 months, the effectiveness of the single-dose measles vaccine was 75% (95% CI = 25–92); vaccination coverage was 68% (95% CI = 61–76).ConclusionsLow vaccine effectiveness, inadequate vaccination coverage and congregation at water collection points facilitated measles transmission in this outbreak. We recommended increasing measles vaccination coverage and restriction of children with signs and symptoms of measles from accessing public gatherings.Electronic supplementary materialThe online version of this article (10.1186/s12879-018-3304-5) contains supplementary material, which is available to authorized users.

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Background Drug-resistant tuberculosis (DR-TB), including rifampicin-resistant tuberculosis (RR-TB) and multidrug-resistant tuberculosis (MDR-TB, or RR-TB with additional isoniazid resistance), presents challenges to TB control. In Uganda, the GeneXpert test provides point-of-care testing for TB and rifampicin resistance. Patients identified with RR-TB receive culture-based drug susceptibility testing (DST) to identify additional resistance, if any. There are few data on the epidemiological profiles of current DR-TB patients in Uganda. We described patients with RR-TB in Uganda and assessed the trends of RR-TB to inform TB control interventions. Methods We identified patients with RR-TB whose samples were referred for culture and DST during 2014–2018 from routinely-generated laboratory surveillance data at the Uganda National Tuberculosis Reference Laboratory. Data on patient demographics and drug sensitivity profile of Mycobacterium tuberculosis isolates were abstracted. Population data were obtained from the Uganda Bureau of Statistics to calculate incidence. Descriptive epidemiology was performed, and logistic regression used to assess trends. Results We identified 1474 patients whose mean age was 36 ± 17 years. Overall incidence was 3.8/100,000 population. Males were more affected by RR-TB than females (4.9 vs. 2.7/100,000, p ≤ 0.01). Geographically, Northern Uganda was the most affected region (IR = 6.9/100,000) followed by the Central region (IR = 5.01/100,000). The overall population incidence of RR-TB increased by 20% over the evaluation period (OR = 1.2; 95% CI 1.15–1.23); RR-TB in new TB cases increased by 35% (OR = 1.35; 95% CI 1.3–1.4) and by 7% in previously-treated cases (OR = 1.07; 95% CI 1.0–1.1). Of the 1474 patients with RR-TB, 923 (63%) were culture-positive of whom 670 (72%) had full DST available. Based on the DST results, 522/670 (78%) had MDR-TB. Conclusion Between 2014 and 2018, the incidence of RR-TB increased especially among newly-diagnosed TB patients. We recommend intensified efforts and screening for early diagnosis especially among previously treated patients. Mechanisms should be in put to ensure that all patients with RR-TB obtain DST.

Background Second-line drug resistance (SLD) among tuberculosis (TB) patients is a serious emerging challenge towards global control of the disease. We characterized SLD-resistance conferring-mutations among TB patients with rifampicin and/or isoniazid (RIF and/or INH) drug-resistance tested at the Uganda National TB Reference Laboratory (NTRL) between June 2017 and December 2019. Methods This was a descriptive cross-sectional secondary data analysis of 20,508 M. tuberculosis isolates of new and previously treated patients’ resistant to RIF and/or INH. DNA strips with valid results to characterise the SLD resistance using the commercial Line Probe Assay Genotype MTBDRsl Version 2.0 Assay (Hain Life Science, Nehren, Germany) were reviewed. Data were analysed with STATAv15 using cross-tabulation for frequency and proportions of known resistance-conferring mutations to injectable agents (IA) and fluoroquinolones (FQ). Results Among the eligible participants, 12,993/20,508 (63.4%) were male and median (IQR) age 32 (24–43). A total of 576/20,508 (2.8%) of the M. tuberculosis isolates from participants had resistance to RIF and/or INH. These included; 102/576 (17.7%) single drug-resistant and 474/576 (82.3%) multidrug-resistant (MDR) strains. Only 102 patients had test results for FQ of whom 70/102 (68.6%) and 01/102 (0.98%) had resistance-conferring mutations in the gyrA locus and gyrB locus respectively. Among patients with FQ resistance, gyrAD94G 42.6% (30.0–55.9) and gyrA A90V 41.1% (28.6–54.3) mutations were most observed. Only one mutation, E540D was detected in the gyrB locus. A total of 26 patients had resistance-conferring mutations to IA in whom, 20/26 77.0% (56.4–91.0) had A1401G mutation in the rrs gene locus. Conclusions Our study reveals a high proportion of mutations known to confer high-level fluoroquinolone drug-resistance among patients with rifampicin and/or isoniazid drug resistance. Utilizing routinely generated laboratory data from existing molecular diagnostic methods may aid real-time surveillance of emerging tuberculosis drug-resistance in resource-limited settings.

BackgroundLeprosy is a neglected disease that poses a significant challenge to public health in Uganda. The disease is endemic in Uganda, with 40% of the districts in the country affected in 2016, when 42 out of 112 districts notified the National Tuberculosis and Leprosy Program (NTLP) of at least one case of leprosy. We determined the spatial and temporal trends of leprosy in Uganda during 2012–2016 to inform control measures.MethodsWe analyzed quarterly leprosy case-finding data, reported from districts to the Uganda National Leprosy Surveillance system (managed by NTLP) during 2012–2016. We calculated new case detection by reporting district and administrative regions of treatment during this period. New case detection was defined as new leprosy cases diagnosed by the Uganda health services divided by regional population; population estimates were based on 2014 census data. We used logistic regression analysis in Epi-Info version 7.2.0 to determine temporal trends. Population estimates were based on 2014 census data. We used QGIS software to draw choropleth maps showing leprosy case detection rates, assumed to approximate the new case detection rates, per 100,000 population.ResultsDuring 2012–2016, there was 7% annual decrease in reported leprosy cases in Uganda each year (p = 0.0001), largely driven by declines in the eastern (14%/year, p = 0.0008) and central (11%/year, p = 0.03) regions. Declines in reported cases in the western (9%/year, p = 0.12) and northern (4%/year, p = 0.16) regions were not significant. The combined new case detection rates from 2012 to 2016 for the ten most-affected districts showed that 70% were from the northern region, 20% from the eastern, 10% from the western and 10% from the central regions.ConclusionThere was a decreasing trend in leprosy new case detection in Uganda during 2012–2016; however, the declining trends were not consistent in all regions. The Northern region consistently identified more leprosy cases compared to the other regions. We recommend evaluation of the leprosy surveillance system to ascertain the leprosy situation.