Investigating Barriers to Tuberculosis Evaluation in Uganda Using Geographic Information Systems

Geographic availability of and physical accessibility to tuberculosis diagnostic tests in Ghana: a cross-sectional survey

BACKGROUND

In Ghana, tuberculosis (TB) case detection is low (< 34%). Existing scientific evidence suggest access to TB diagnostic tests play an essential role in TB case detection, yet little has been scientifically documented on it in Ghana. This study, therefore, sought to map TB diagnosis sites, and describe the geographic availability and physical accessibility to TB diagnosis in six regions of Ghana to inform scale-up and future placement of TB diagnostic tests.

METHODS

We assembled the geolocation and attribute data of all health facilities offering TB diagnosis in Upper West Region (UWR), Upper East Region (UER), Ahafo, North-East, Northern, and Savannah regions. QGIS was employed to estimate the distance and travel time to TB diagnosis sites within regions. Travel time estimates were based on assumed motorised tricycle speed of 20 km (km)/hour.

RESULTS

Of the total 1584 health facilities in the six regions, 86 (5.4%) facilities were providing TB diagnostic testing services. This 86 TB diagnosis sites comprised 56 (65%) microscopy sites, 23 (27%) both microscopy and GeneXpert sites, and 7 (8%) GeneXpert only sites (8%). Of the 86 diagnosis sites, 40 (46%) were in the UER, follow by Northern Region with 16 (19%), 12 (14%) in UWR, 9 (10%) in Ahafo Region, 5 (6%) in North East, and 4 (5%) in Savannah Region. The overall estimated mean distance and travel time to the nearest TB diagnosis site was 23.3 ± 13.8 km and 67.6 ± 42.6 min respectively. Savannah Region recorded the longest estimated mean distance and travel time with 36.1 ± 14.6 km and 108.3 ± 43.9 min, whilst UER recorded the shortest with 10.2 ± 5.8 km and 29.1 ± 17.4 min. Based on a 10 km buffer of settlement areas, an estimated 75 additional TB diagnosis sites will be needed to improve access to TB diagnosis services across the six regions.

CONCLUSION

This study highlights limited availability of TB diagnosis sites and poor physical accessibility to TB diagnosis sites across five out of the six regions. Targeted implementation of additional TB diagnosis sites is needed to reduce travel distances to ≤ 10 km.

Gaps related to screening and diagnosis of tuberculosis in care cascade in selected health facilities in East Africa countries: A retrospective study

Introduction

East Africa countries (Tanzania, Kenya, and Uganda) are among tuberculosis high burdened countries globally. As we race to accelerate progress towards a world free of tuberculosis by 2035, gaps related to screening and diagnosis in the cascade care need to be addressed.

Methods

We conducted a three-year (2015–2017) retrospective study using routine program data in 21 health facilities from East Africa. Data abstraction were done at tuberculosis clinics, outpatient departments (OPD), human immunodeficiency virus (HIV) and diabetic clinics, and then complemented with structured interviews with healthcare providers to identify possible gaps related to integration, screening, and diagnosis of tuberculosis. Data were analyzed using STATA™ Version 14.1.

Results

We extracted information from 49,454 presumptive TB patients who were registered in the 21 facilities between January 2015 and December 2017. A total of 9,565 tuberculosis cases were notified; 46.5% (4,450) were bacteriologically confirmed and 31.5% (3,013) were HIV-infected. Prevalence of tuberculosis among presumptive pulmonary tuberculosis cases was 17.4%. The outcomes observed were as follows: 79.8% (7,646) cured or completed treatment, 6.6% (634) died, 13.3% (1,270) lost to follow-up or undocumented and 0.4% (34) treatment failure. In all countries, tuberculosis screening was largely integrated at OPD and HIV clinics. High patient load, weak laboratory specimen referral system, shortage of trained personnel, and frequent interruption of laboratory supplies were the major cited challenges in screening and diagnosis of tuberculosis.

Conclusion

Screening and diagnostic activities were frequently affected by scarcity of human and financial resources. Tuberculosis screening was mainly integrated at OPD and HIV clinics, with less emphasis on the other health facility clinics. Closing gaps related to TB case finding and diagnosis in developing countries requires sustainable investment for both human and financial resources and strengthen the integration of TB activities within the health system.

Validating the Global Surgery Geographical Accessibility Indicator: Differences in Modeled Versus Patient-Reported Travel Times

Background

Since long travel times to reach health facilities are associated with worse outcomes, geographic accessibility is one of the six core global surgery indicators; this corresponds to the second of the “Three Delays Framework,” namely “delay in reaching a health facility.” Most attempts to estimate this indicator have been based on geographical information systems (GIS) algorithms. The aim of our study was to compare GIS derived estimates to self-reported travel times for patients traveling to a district hospital in rural Rwanda for emergency obstetric care.

Methods

Our study includes 664 women who traveled to undergo a Cesarean delivery in Kirehe, Rwanda. We compared self-reported travel time from home to the hospital (excluding waiting time) with GIS estimated travel times, which were computed using the World Health Organization tool AccessMod, using linear regression.

Results

The majority of patients used multiple modes of transportation (walking = 48.5%, public transport = 74.2%, private transport = 2.9%, and ambulance 70.6%). Self-reported times were longer than GIS estimates by a factor of 1.49 (95% CI 1.40–1.57). Concordance was higher when the GIS model took into account that all patients in Rwanda are referred via their health center (β = 1.12; 95% CI 1.05–1.18).

Conclusions

To our knowledge, in this largest to date GIS validation study for geographical access to healthcare in low- and middle-income countries, a standard GIS model was found to significantly underestimate real travel time, which likely is in part because it does not model the actual route patients are travelling. Therefore, previous studies of 2-h access to surgery will need to be interpreted with caution, and future studies should take local travelling conditions into account.

Electronic supplementary material

The online version of this article (10.1007/s00268-020-05480-8) contains supplementary material, which is available to authorized users.

Patient and health system factors associated with pretreatment loss to follow up among patients diagnosed with tuberculosis using Xpert® MTB/RIF testing in Uganda

BACKGROUND

In 2018, Uganda started only 65% of persons with incident tuberculosis on treatment. Pretreatment loss to follow up is an important contributor to suboptimal treatment coverage. We aimed to describe the patient and health facility-level characteristics associated with pretreatment loss to follow up among patients diagnosed with pulmonary tuberculosis at public health facilities in Uganda.

METHODS

At ten public health facilities, laboratory register data was used to identify patients aged ≥ 15 years who had a positive Xpert®MTB/RIF test. Initiation on TB treatment was ascertained using the clinical register. Factors associated with not being initiated on TB treatment within two weeks of diagnosis were examined using a multilevel logistic regression model accounting for clustering by health facility.

RESULTS

From January to June 2018, 510 patients (61.2% male and 31.5% HIV co-infected) were diagnosed with tuberculosis. One hundred (19.6%) were not initiated on TB treatment within 2 weeks of diagnosis. Not having a phone number recorded in the clinic registers (aOR 7.93, 95%CI 3.93-13.05); being HIV-infected (aOR 1.83; 95% CI: 1.09-3.26) and receiving care from a high volume health facility performing more than 12 Xpert tests per day (aOR 4.37, 95%CI 1.69-11.29) and were significantly associated with pretreatment loss to follow up.

CONCLUSION

In public health facilities in Uganda, we found a high rate of pretreatment loss to follow up especially among TBHIV co-infected patients diagnosed at high volume health facilities. Interventions to improve the efficiency of Xpert® MTB/RIF testing, including monitoring of the TB care cascade should be developed and implemented.

Patient and health system factors associated with pretreatment loss to follow up among patients diagnosed with tuberculosis using Xpert® MTB/RIF testing in Uganda

Background

In 2018, Uganda started only 65% of persons with incident tuberculosis on treatment. Pretreatment loss to follow up is an important contributor to suboptimal treatment coverage. We aimed to describe the patient and health facility-level characteristics associated with pretreatment loss to follow up among patients diagnosed with pulmonary tuberculosis at public health facilities in Uganda.

Methods

At ten public health facilities, laboratory register data was used to identify patients aged ≥ 15 years who had a positive Xpert®MTB/RIF test. Initiation on TB treatment was ascertained using the clinical register. Factors associated with not being initiated on TB treatment within two weeks of diagnosis were examined using a multilevel logistic regression model accounting for clustering by health facility.

Results

From January to June 2018, 510 patients (61.2% male and 31.5% HIV co-infected) were diagnosed with tuberculosis. One hundred (19.6%) were not initiated on TB treatment within 2 weeks of diagnosis. Not having a phone number recorded in the clinic registers (aOR 7.93, 95%CI 3.93–13.05); being HIV-infected (aOR 1.83; 95% CI: 1.09–3.26) and receiving care from a high volume health facility performing more than 12 Xpert tests per day (aOR 4.37, 95%CI 1.69–11.29) and were significantly associated with pretreatment loss to follow up.

Conclusion

In public health facilities in Uganda, we found a high rate of pretreatment loss to follow up especially among TBHIV co-infected patients diagnosed at high volume health facilities. Interventions to improve the efficiency of Xpert® MTB/RIF testing, including monitoring of the TB care cascade should be developed and implemented.

Is distance associated with tuberculosis treatment outcomes? A retrospective cohort study in Kampala, Uganda

Background

Challenges accessing nearby health facilities may be a barrier to initiating and completing tuberculosis (TB) treatment. We aimed to evaluate whether distance from residence to health facility chosen for treatment is associated with TB treatment outcomes.

Methods

We conducted a retrospective cohort study of all patients initiating TB treatment at six health facilities in Kampala from 2014 to 2016. We investigated associations between distance to treating facility and unfavorable TB treatment outcomes (death, loss to follow up, or treatment failure) using multivariable Poisson regression.

Results

Unfavorable treatment outcomes occurred in 20% (339/1691) of TB patients. The adjusted relative risk (aRR) for unfavorable treatment outcomes (compared to treatment success) was 0.87 (95% confidence interval [CI] 0.70, 1.07) for patients living ≥2 km from the facility compared to those living closer. When we separately compared each type of unfavorable treatment outcome to favorable outcomes, those living ≥2 km from the facility had increased risk of death (aRR 1.42 [95%CI 0.99, 2.03]) but decreased risk for loss to follow-up (aRR 0.57 [95%CI 0.41, 0.78]) than those living within 2 km.

Conclusions

Distance from home residence to TB treatment facility is associated with increased risk of death but decreased risk of loss to follow up. Those who seek care further from home may have advanced disease, but once enrolled may be more likely to remain in treatment.

Geographic accessibility to public health facilities providing tuberculosis testing services at point-of-care in the upper east region, Ghana

BACKGROUND

In Ghana, limited evidence exists about the geographical accessibility to health facilities providing tuberculosis (TB) diagnostic services to facilitate early diagnosis and treatment. Therefore, we aimed to assess the geographic accessibility to public health facilities providing TB testing services at point-of-care (POC) in the Upper East Region (UER), Ghana.

METHODS

We assembled detailed spatial data on all 10 health facilities providing TB testing services at POC, and landscape features influencing journeys. These data were used in a geospatial model to estimate actual distance and travel time from the residential areas of the population to health facilities providing TB testing services. Maps displaying the distance values were produced using ArcGIS Desktop v10.4. Spatial distribution of the health facilities was done using spatial autocorrelation (Global Moran's Index) run in ArcMap 10.4.1. We also applied remote sensing through satellite imagery analysis to map out residential areas and identified locations for targeted improvement in the UER.

RESULTS

Of the 13 districts in the UER, 4 (31%) did not have any health facility providing TB testing services. In all, 10 public health facilities providing TB testing services at POC were available in the region representing an estimated population to health facility ratio of 125,000 people per facility. Majority (60%) of the health facilities providing TB testing services in the region were in districts with a total population greater than 100,000 people. Majority (62%) of the population resident in the region were located more than 10 km away from a health facility providing TB testing services. The mean distance ± standard deviation to the nearest public health facility providing TB testing services in UER was 33.2 km ± 13.5. Whilst the mean travel time using a motorized tricycle speed of 20 km/h to the nearest facility providing TB testing services in the UER was 99.6 min ± 41.6. The results of the satellite imagery analysis show that 51 additional health facilities providing TB testing services at POC are required to improve geographical accessibility. The results of the spatial autocorrelation analysis show that the spatial distribution of the health facilities was dispersed (z-score = - 2.3; p = 0.02).

CONCLUSION

There is poor geographic accessibility to public health facilities providing TB testing services at POC in the UER of Ghana. Targeted improvement of rural PHC clinics in the UER to enable them provide TB testing services at POC is highly recommended.

Why does it take so long? The reasons behind tuberculosis treatment delay in Portugal

INTRODUCTION

Delayed diagnosis and treatment of tuberculosis contributes to the spread of the disease. In this study, we aimed to determine the patient and healthcare system delay among tuberculosis patients in Portugal and identify associated factors at individual and contextual level.

METHODS

We analysed all TB cases notified in Portugal between 2010 and 2014 using data from the national surveillance system. Patient and healthcare system delay were computed, log-transformed, and used as outcomes. Adjusted generalized linear models were fitted to identify sociodemographic, contextual and clinical determinants.

RESULTS

The study included 6838 patients. The median of patient and healthcare system were 33 and 17 days, respectively. Adjusted regression models revealed that higher patient delay occurred in foreign patients (exponentiated beta: 1.177, 95%CI 1.091-1.270) and those addicted to alcohol (1.169, 1.072-1.276) and drugs (1.153, 1.027-1.295). Higher healthcare system delay was observed among patients with extra-pulmonary TB (2.067, 1.885-2.268) and pulmonary comorbidities - lung cancer (2.391, 1.656-3.452), sarcoidosis (3.316, 1.370-8.022) and COPD (1.295, 1.059-1.584) - and in patients residing further from a healthcare service (1.040, 1.018-1.062).

CONCLUSION

We found that various individual and contextual factors affect the time delay in tuberculosis treatment. Our findings indicate that some strategies, such as facilitating the access to healthcare services among foreign patients and patients with addictions and increasing the awareness towards TB among healthcare professionals, may result in better TB control.

Methods used in the spatial analysis of tuberculosis epidemiology: a systematic review

BACKGROUND

Tuberculosis (TB) transmission often occurs within a household or community, leading to heterogeneous spatial patterns. However, apparent spatial clustering of TB could reflect ongoing transmission or co-location of risk factors and can vary considerably depending on the type of data available, the analysis methods employed and the dynamics of the underlying population. Thus, we aimed to review methodological approaches used in the spatial analysis of TB burden.

METHODS

We conducted a systematic literature search of spatial studies of TB published in English using Medline, Embase, PsycInfo, Scopus and Web of Science databases with no date restriction from inception to 15 February 2017. The protocol for this systematic review was prospectively registered with PROSPERO ( CRD42016036655 ).

RESULTS

We identified 168 eligible studies with spatial methods used to describe the spatial distribution (n = 154), spatial clusters (n = 73), predictors of spatial patterns (n = 64), the role of congregate settings (n = 3) and the household (n = 2) on TB transmission. Molecular techniques combined with geospatial methods were used by 25 studies to compare the role of transmission to reactivation as a driver of TB spatial distribution, finding that geospatial hotspots are not necessarily areas of recent transmission. Almost all studies used notification data for spatial analysis (161 of 168), although none accounted for undetected cases. The most common data visualisation technique was notification rate mapping, and the use of smoothing techniques was uncommon. Spatial clusters were identified using a range of methods, with the most commonly employed being Kulldorff's spatial scan statistic followed by local Moran's I and Getis and Ord's local Gi(d) tests. In the 11 papers that compared two such methods using a single dataset, the clustering patterns identified were often inconsistent. Classical regression models that did not account for spatial dependence were commonly used to predict spatial TB risk. In all included studies, TB showed a heterogeneous spatial pattern at each geographic resolution level examined.

CONCLUSIONS

A range of spatial analysis methodologies has been employed in divergent contexts, with all studies demonstrating significant heterogeneity in spatial TB distribution. Future studies are needed to define the optimal method for each context and should account for unreported cases when using notification data where possible. Future studies combining genotypic and geospatial techniques with epidemiologically linked cases have the potential to provide further insights and improve TB control.

Social determinants of tuberculosis evaluation among household contacts: a secondary analysis

Setting: Seven public sector tuberculosis (TB) units and surrounding communities in Kampala, Uganda. Objective: To evaluate the influence of household-level socio-economic characteristics on completion of TB evaluation during household contact investigation. Design: A cross-sectional study nested within the control arm of a randomized, controlled trial evaluating home-based sputum collection and short messaging service communications. We used generalized estimating equations to estimate the association between completion of TB evaluation and socio-economic determinants. Results: Of 116 household contacts referred to clinics for TB evaluation, 32 (28%) completed evaluation. Completing evaluation was strongly clustered by household. Controlling for individual symptoms, contacts from households earning below-median income (adjusted risk ratio [aRR] 0.28, 95%CI 0.09-0.88, P = 0.029) and contacts from households in which the head of household had no more than primary-level education (aRR 0.40, 95%CI 0.18-0.89, P = 0.025) were significantly less likely to complete evaluation for TB. Conclusion: Socio-economic factors such as low income and education increase the risk that household contacts of TB patients will experience barriers to completing TB evaluation themselves. Further research is needed to identify specific mechanisms by which these underlying social determinants modify the capability and motivation of contacts to complete contact investigation.

Tuberculosis treatment success among rural and urban Ugandans living with HIV: a retrospective study

Setting: Government health centres and hospitals (six urban and 20 rural) providing tuberculosis (TB) treatment for people living with the human immunodeficiency virus (PLHIV) in central and western Uganda. Objective: To identify and quantify modifiable factors that limit TB treatment success among PLHIV in rural Uganda. Design: A retrospective cross-sectional review of routine Uganda National Tuberculosis and Leprosy Programme clinic registers and patient files of HIV-positive patients who received anti-tuberculosis treatment in 2014. Results: Of 191 rural patients, 66.7% achieved treatment success compared to 81.1% of 213 urban patients. Adjusted analysis revealed higher average treatment success in urban patients than in rural patients (OR 3.95, 95%CI 2.70-5.78, P < 0.01, generalised estimating equation model). Loss to follow-up was higher and follow-up sputum smear results were less frequently recorded in TB clinic registers among rural patients. Patients receiving treatment at higher-level facilities in rural settings had greater odds of treatment success, while patients receiving treatment at facilities where drug stock-outs had occurred had lower odds of treatment success. Conclusion: Lower reported treatment success in rural settings is mainly attributed to clinic-centred factors such as treatment monitoring procedures. We recommend strengthening treatment monitoring and delivery.

Barriers to initiating tuberculosis treatment in sub-Saharan Africa: a systematic review focused on children and youth

BACKGROUND

Tuberculosis (TB) is the deadliest infectious disease globally, with 10.4 million people infected and more than 1.8 million deaths in 2015. TB is a preventable, treatable, and curable disease, yet there are numerous barriers to initiating treatment. These barriers to treatment are exacerbated in low-resource settings and may be compounded by factors related to childhood.

OBJECTIVE

Timely initiation of tuberculosis (TB) treatment is critical to reducing disease transmission and improving patient outcomes. The aim of this paper is to describe patient- and system-level barriers to TB treatment initiation specifically for children and youth in sub-Saharan Africa through systematic review of the literature.

DESIGN

This review was conducted in October 2015 in accordance with preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Six databases were searched to identify studies where primary or secondary objectives were related to barriers to TB treatment initiation and which included children or youth 0-24 years of age.

RESULTS

A total of 1490 manuscripts met screening criteria; 152 met criteria for full-text review and 47 for analysis. Patient-level barriers included limited knowledge, attitudes and beliefs regarding TB, and economic burdens. System-level barriers included centralization of services, health system delays, and geographical access to healthcare. Of the 47 studies included, 7 evaluated cost, 19 health-seeking behaviors, and 29 health system infrastructure. Only 4 studies primarily assessed pediatric cohorts yet all 47 studies were inclusive of children.

CONCLUSIONS

Recognizing and removing barriers to treatment initiation for pediatric TB in sub-Saharan Africa are critical. Both patient- and system-level barriers must be better researched in order to improve patient outcomes.