Accessibility to tuberculosis control services and tuberculosis programme performance in southern Ethiopia

Association between TB delay and TB treatment outcomes in HIV-TB co-infected patients: a study based on the multilevel propensity score method

BACKGROUND

HIV-tuberculosis (HIV-TB) co-infection is a significant public health concern worldwide. TB delay, consisting of patient delay, diagnostic delay, treatment delay, increases the risk of adverse anti-TB treatment (ATT) outcomes. Except for individual level variables, differences in regional levels have been shown to impact the ATT outcomes. However, few studies appropriately considered possible individual and regional level confounding variables. In this study, we aimed to assess the association of TB delay on treatment outcomes in HIV-TB co-infected patients in Liangshan Yi Autonomous Prefecture (Liangshan Prefecture) of China, using a causal inference framework while taking into account individual and regional level factors.

METHODS

We conducted a study to analyze data from 2068 patients with HIV-TB co-infection in Liangshan Prefecture from 2019 to 2022. To address potential confounding bias, we used a causal directed acyclic graph (DAG) to select appropriate confounding variables. Further, we controlled for these confounders through multilevel propensity score and inverse probability weighting (IPW).

RESULTS

The successful rate of ATT for patients with HIV-TB co-infection in Liangshan Prefecture was 91.2%. Total delay (OR = 1.411, 95% CI: 1.015, 1.962), diagnostic delay (OR = 1.778, 95% CI: 1.261, 2.508), treatment delay (OR = 1.749, 95% CI: 1.146, 2.668) and health system delay (OR = 1.480 95% CI: (1.035, 2.118) were identified as risk factors for successful ATT outcome. Sensitivity analysis demonstrated the robustness of these findings.

CONCLUSIONS

HIV-TB co-infection prevention and control policy in Liangshan Prefecture should prioritize early treatment for diagnosed HIV-TB co-infected patients. It is urgent to improve the health system in Liangshan Prefecture to reduce delays in diagnosis and treatment.

Effectiveness of Using AI-Driven Hotspot Mapping for Active Case Finding of Tuberculosis in Southwestern Nigeria

Background: Nigeria is among the top five countries that have the highest gap between people reported as diagnosed and estimated to have developed tuberculosis (TB). To bridge this gap, there is a need for innovative approaches to identify geographical areas at high risk of TB transmission and targeted active case finding (ACF) interventions. Leveraging community-level data together with granular sociodemographic contextual information can unmask local hotspots that could be otherwise missed. This work evaluated whether this approach helps to reach communities with higher numbers of undiagnosed TB. Methodology: A retrospective analysis of the data generated from an ACF intervention program in four southwestern states in Nigeria was conducted. Wards (the smallest administrative level in Nigeria) were further subdivided into smaller population clusters. ACF sites and their respective TB screening outputs were mapped to these population clusters. This data were then combined with open-source high-resolution contextual data to train a Bayesian inference model. The model predicted TB positivity rates on the community level (population cluster level), and these were visualised on a customised geoportal for use by the local teams to identify communities at high risk of TB transmission and plan ACF interventions. The TB positivity yield (proportion) observed at model-predicted hotspots was compared with the yield obtained at other sites identified based on aggregated notification data. Results: The yield in population clusters that were predicted to have high TB positivity rates by the model was at least 1.75 times higher (p-value < 0.001) than the yield in other locations in all four states. Conclusions: The community-level Bayesian predictive model has the potential to guide ACF implementers to high-TB-positivity areas for finding undiagnosed TB in the communities, thus improving the efficiency of interventions.

Spatio-Temporal Pattern of Tuberculosis Distribution in Romania and Particulate Matter Pollution Associated With Risk of Infection

The study proposes a dynamic spatio-temporal profile of the distribution of tuberculosis incidence and air pollution in Romania, where this infectious disease induces more than 8,000 new cases annually. The descriptive analysis for the years 2012-2021 assumes an identification of the structuring patterns of mycobacterium tuberculosis risk in the Romanian population, according to gender and age, exploiting spatial modeling techniques of time series data. Through spatial autocorrelation, the degree of similarity between the analyzed territorial systems was highlighted and the relationships that are built between the analysis units in spatial proximity were investigated. By modeling the geographical distribution of tuberculosis, the spatial correlation with particulate matter (PM2.5) pollution was revealed. The identification of clusters of infected persons is an indispensable step in the construction of efficient tuberculosis management systems. The results highlight the link between the distribution of tuberculosis, air pollution and socio-economic development, which requires a detailed analysis of the epidemiological data obtained in the national tuberculosis surveillance and control program from the perspective of geographical distribution.

Development and validation of a risk prediction model for pulmonary tuberculosis among presumptive tuberculosis cases in Ethiopia

BACKGROUND

Early diagnosis and treatment of tuberculosis (TB) is one of the key strategies to achieve the WHO End TB targets. This study aimed to develop and validate a simple, convenient risk score to diagnose pulmonary TB among presumptive TB cases.

METHODS

This prediction model used Ethiopian national TB prevalence survey data and included 5459 presumptive TB cases from all regions of Ethiopia. Logistic regression was used to determine which variables are predictive of pulmonary TB. A risk prediction model was developed, incorporating significant variables (p<0.05). The Youden Index method was used to choose the optimal cut-off point to separate the risk score of the patients as high and low. Model performance was assessed using discrimination power and calibration. Internal validation of the model was assessed using Efron's enhanced bootstrap method, and the clinical utility of the risk score was assessed using decision curve analysis.

RESULTS

Of total participants, 94 (1.7%) were confirmed to have TB. The final prediction model included three factors with different scores: (1) TB contact history, (2) chest X-ray (CXR) abnormality and (3) two or more symptoms of TB. The optimal cut-off point for the risk score was 6 and was found to have a good discrimination accuracy (c-statistic=0.70, 95% CI: 0.65 to 0.75). The risk score has sensitivity of 51.1%, specificity of 79.9%, positive predictive value of 4.3% and negative predictive value of 98.9%. After internal validation, the optimism coefficient was 0.003, which indicates the model is internally valid.

CONCLUSION

We developed a risk score that combines TB contact, number of TB symptoms and CXR abnormality to estimate individual risk of pulmonary TB among presumptive TB cases. Though the score is easy to calculate and internally validated, it needs external validation before widespread implementation in a new setting.

Spatiotemporal Distribution of Tuberculosis in the Oromia Region of Ethiopia: A Hotspot Analysis

Tuberculosis (TB) is a major public health concern in low- and middle-income countries including Ethiopia. This study aimed to assess the spatiotemporal distribution of TB and identify TB risk factors in Ethiopia's Oromia region. Descriptive and spatiotemporal analyses were conducted. Bayesian spatiotemporal modeling was used to identify covariates that accounted for variability in TB and its spatiotemporal distribution. A total of 206,278 new pulmonary TB cases were reported in the Oromia region between 2018 and 2022, with the lowest annual TB case notification (96.93 per 100,000 population) reported in 2020 (i.e., during the COVID-19 pandemic) and the highest TB case notification (106.19 per 100,000 population) reported in 2019. Substantial spatiotemporal variations in the distribution of notified TB case notifications were observed at zonal and district levels with most of the hotspot areas detected in the northern and southern parts of the region. The spatiotemporal distribution of notified TB incidence was positively associated with different ecological variables including temperature (β = 0.142; 95% credible interval (CrI): 0.070, 0.215), wind speed (β = -0.140; 95% CrI: -0.212, -0.068), health service coverage (β = 0.426; 95% CrI: 0.347, 0.505), and population density (β = 0.491; 95% CrI: 0.390, 0.594). The findings of this study indicated that preventive measures considering socio-demographic and health system factors can be targeted to high-risk areas for effective control of TB in the Oromia region. Further studies are needed to develop effective strategies for reducing the burden of TB in hotspot areas.

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.

Assessment of tuberculosis case notification rate: spatial mapping of hotspot, coverage and diagnostics in Katsina State, north-western Nigeria

Tuberculosis (TB) is prevalent in Nigeria, and Katsina, along with other 12 states in the country, accounts for a high proportion of unnotified TB cases: constituting the high priority-intervention States in the country. Interventions focused on TB detection and coverage in the state could benefit from a better understanding of hotspot Local Government Areas (LGAs) that trigger and sustain the disease. Therefore, this study investigated the spatial distribution of TB Case Notification Rates (CNRs), diagnostics and coverage across the LGAs. Using 2017 to 2019 TB case finding data, the geocoordinates of diagnostic facilities and shapefiles, a retrospective ecological study was conducted. The data were analysed with QGIS and GeoDa. Moran's I and LISA were used to locate and quantify hotspots. The coverage of microscopy and GeneXpert facilities was assessed on QGIS using a 5 km and 20 km radius, respectively. The CNR in the state, and 29 of the 34 LGAs, increased steadily from 2017 to 2019. Hotspots of high CNRs were also identified in 2017 (Moran's I=0.106, p-value=0.090) and 2018 (Moran's I=-0.020, p-value=0.370). While CNRs increased along with presumptive TB rates across most LGAs over the years, the positivity yield and bacteriological and Xpert diagnostic rates decreased. Bacteriological and GeneXpert coverage were 78% and 49% respectively. Additionally, only 51% of the state's population lived within 20km of a GeneXpert facility. These results suggest that TB program interventions had some positive impact on the CNR, however, diagnostic facilities need to be equitably distributed and more innovative approaches need to be explored to find the missing cases.

Performance evaluation of tuberculosis control in Brazilian municipalities

OBJECTIVE

To evaluate the performance of tuberculosis control in Brazilian municipalities.

METHODS

This is an ecological study on Brazilian municipalities that notified at least four new cases of tuberculosis, with a minimum of one new case of pulmonary tuberculosis between 2015 and 2018. The municipalities were stratified according to the population in < 50 thousand, 50-100 thousand, 100-300 thousand, and > 300 thousand inhabitants, and the k-means method was used to group them within each population range according to the performance of six indicators of the disease.

RESULTS

A total of 2,845 Brazilian municipalities were included, comprising 98.5% (208,007/211,174) of new tuberculosis cases in the period. For each population range, three groups (A, B, and C) of municipalities were identified according to the performance of the indicators: A, the most satisfactory; B, the intermediates; and C, the least satisfactory. Municipalities in group A with < 100 thousand inhabitants presented results above the targets for laboratory confirmation (≥ 72%), abandonment (≤ 5%), and cure (≥ 90%), and comprised 2% of new cases of the disease. Conversely, municipalities of groups B and C presented at least five indicators with results below the targets - HIV testing (< 100%), contact investigation (< 90%), directly observed therapy (< 90%), abandonment (> 5%), and cure (< 90%) -, and corresponded to 66.7% of new cases of tuberculosis. In group C of municipalities with > 300 thousand inhabitants, which included 19 of the 27 capitals and 43.1% of new cases of tuberculosis, the lowest percentages of contact investigation (mean = 56.4%) and directly observed therapy (mean = 15.4%) were verified, in addition to high abandonment (mean = 13.9%) and low coverage of primary health care (mean = 66.0%).

CONCLUSIONS

Most new cases of tuberculosis occurred in municipalities with unsatisfactory performance for disease control. Expanding the coverage of primary health care in these places can reduce abandonment and increase the contact investigation and directly observed therapy.

The dynamic impacts of environmental-health and MDR-TB diseases and their influence on environmental sustainability at Chinese hospitals

The purpose of this study is to identify at what extent multidrug-resistant tuberculosis (MDR-TB) diseases effect on environmental health issues in selected provinces of Chinese hospitals. In survival analysis approach, this study employs the Cox proportional hazard model (CPM) to incorporate the duration of event, probability of occurrence of an event, and the issue of right censoring. An advantage of using CPM is that one does not need to specify the distribution of baseline hazard H₀ (t) as it considers a common value for all units in population. The results indicate that male and travel expenditures have negative association with the duration of cure. Furthermore, the medical expenditures and the spatial characteristic of time expenditure have positive association with the duration of cure of MDR-TB patients. The inconsistent behavior of males in taking medicines as compared to females and males is also more prone to tuberculosis (TB).

Geographic accessibility to health facilities predicts uptake of community-based tuberculosis screening in an urban setting

Objectives:

Annually, more than 30% of individuals with tuberculosis (TB) remain undiagnosed. We aimed to assess whether geographic accessibility measures can identify neighborhoods that would benefit from TB screening services targeted toward closing the diagnosis gap.

Methods:

We used data from a community-based mobile TB screening program in Carabayllo district, Lima, Peru. We constructed four accessibility measures from the geographic center of neighborhoods to health facilities. We used logistic regression to assess the association between these measures and screening uptake in one’s residential neighborhood versus elsewhere, with quasi-information criterion values to assess the association.

Results:

We analyzed the screening locations for 25,000 Carabayllo residents from 49 neighborhoods. Pedestrian walk time was preferable to Euclidean distance or vehicular time in our models. For each additional 12 minutes walking time between the neighborhood and the health facility, the odds of residents using TB screening units located in their neighborhoods increased by 50% (95% CI: 26%–78%). Females had 9% (95% CI: 3%–16%) increased odds versus males of using a screening unit in their own neighborhood.

Conclusion:

Placing mobile TB screening units in neighborhoods with longer pedestrian time to access health facilities could benefit individuals who face more acute access barriers to health care.

Missed Tuberculosis Investigations and Associated Factors in Patients with Symptoms Indicative of Tuberculosis at Public Health Institutions in Northwest Ethiopia: The Application of a Negative Binomial Model

Background

Tuberculosis (TB) remains one of the top health problems in Ethiopia, and over one-third of estimated TB cases remain undetected. This study examined the magnitude and factors of missed opportunities for TB investigation at public health facilities in Northwest Ethiopia.

Methods

A facility-based cross-sectional study was conducted among 412 adult patients with TB symptoms from 34 randomly selected public health facilities. Data on socio-demographics, TB symptoms, and clinical status were collected by an exit interview. A patient was considered missed for TB investigation if he/she had at least one symptom suggestive of TB but did not receive a sputum smear and/or x-ray evaluation to rule out TB. We computed descriptive and analytical statistics using SPSS version 26. A negative binomial regression analysis was used to identify factors associated with missed opportunities for TB investigation. Statistical significance was determined at a p-value less than 0.05.

Results

A total of 412 presumptive TB patients, 235 (57%) females and 247 (60%) rural dwellers were interviewed. The mean age of respondents was 35 ± 8 years and 228 (55.3%) were from health centers. Over two-thirds, 284 (69%) were new patients, 62 (15%) were HIV positive and 78 (19%) had diabetes mellitus (DM). Fifty patients with symptoms suggestive of TB did not receive sputum evaluation services. Inability to read and write, having DM, having normal body mass index and facility type they visited were significant factors to missing opportunities to get TB investigations.

Conclusion

A significant number of patients with symptoms suggestive of TB were missed for sputum evaluation to rule out TB. Education level, comorbidity, nutritional status and type of facility patients attended were factors of missing opportunities for TB investigation. Thus, improving quality of TB diagnosis, screening TB among all types of patients, and paying attention to screen illiterate people are crucial to avoid missing potential TB cases.

Mapping local hot spots with routine tuberculosis data: A pragmatic approach to identify spatial variability

Objective

To use routinely collected data, with the addition of geographic information and census data, to identify local hot spots of rates of reported tuberculosis cases.

Design

Residential locations of tuberculosis cases identified from eight public health facilities in Lima, Peru (2013–2018) were linked to census data to calculate neighborhood-level annual case rates. Heat maps of tuberculosis case rates by neighborhood were created. Local indicators of spatial autocorrelation, Moran’s I, were used to identify where in the study area spatial clusters and outliers of tuberculosis case rates were occurring. Age- and sex-stratified case rates were also assessed.

Results

We identified reports of 1,295 TB cases across 74 neighborhoods during the five-year study period, for an average annual rate of 124.2 reported TB cases per 100,000 population. In evaluating case rates by individual neighborhood, we identified a median rate of reported cases of 123.6 and a range from 0 to 800 cases per 100,000 population. Individuals aged 15–44 years old and men had higher case rates than other age groups and women. Locations of both hot and cold spots overlapped across age- and gender-specific maps.

Conclusions

There is significant geographic heterogeneity in rates of reported TB cases and evident hot and cold spots within the study area. Characterization of the spatial distribution of these rates and local hot spots may be one practical tool to inform the work of local coalitions to target TB interventions in their zones.

A role for community-level socioeconomic indicators in targeting tuberculosis screening interventions

Tuberculosis screening programs commonly target areas with high case notification rates. However, this may exacerbate disparities by excluding areas that already face barriers to accessing diagnostic services. We compared historic case notification rates, demographic, and socioeconomic indicators as predictors of neighborhood-level tuberculosis screening yield during a mobile screening program in 74 neighborhoods in Lima, Peru. We used logistic regression and Classification and Regression Tree (CART) analysis to identify predictors of screening yield. During February 7, 2019-February 6, 2020, the program screened 29,619 people and diagnosed 147 tuberculosis cases. Historic case notification rate was not associated with screening yield in any analysis. In regression analysis, screening yield decreased as the percent of vehicle ownership increased (odds ratio [OR]: 0.76 per 10% increase in vehicle ownership; 95% confidence interval [CI]: 0.58-0.99). CART analysis identified the percent of blender ownership (≤ 83.1% vs > 83.1%; OR: 1.7; 95% CI: 1.2-2.6) and the percent of TB patients with a prior tuberculosis episode (> 10.6% vs ≤ 10.6%; OR: 3.6; 95% CI: 1.0-12.7) as optimal predictors of screening yield. Overall, socioeconomic indicators were better predictors of tuberculosis screening yield than historic case notification rates. Considering community-level socioeconomic characteristics could help identify high-yield locations for screening interventions.

Treatment outcomes of patients with drug-sensitive tuberculosis under community-based versus facility-based directly observed treatment, short course strategy in Southwest Ethiopia: a prospective cohort study

OBJECTIVE

To compare tuberculosis (TB) treatment outcomes and associated factors among patients attending community-based versus facility-based directly observed treatment, short course (DOTS).

DESIGN

A prospective cohort study.

SETTING

The study was conducted in Southwest Ethiopia. There were seven hospitals (five primary, one general and one specialised), 120 health centres and 494 health posts.

PARTICIPANTS

A total of 1161 individuals consented to participate in the study (387 patients under community-based DOTS (CB-DOTS) and 774 patients under facility-based DOTS (FB-DOTS)). Individuals who could not respond to the questions, mentally or critically ill patients, and those less than 15 years old, were excluded from the study.

PRIMARY OUTCOME MEASURE

TB treatment outcomes were compared among patients under CB-DOTS versus FB-DOTS. Risk ratio (RR), risk difference (RD) and confidence interval (CI) were calculated among the study groups. In addition, χ² or Fisher's exact tests were used to compare group differences, with a p value of <0.05 considered statistically significant.

RESULTS

Patients who opted for CB-DOTS were more likely to be cured by 12% than those who opted for FB-DOTS (RR=1.12, 95% CI=0.96 to 1.30). Patients under CB-DOTS had a lesser risk of death (RR=0.93, 95% CI=0.49 to 1.77) and a lower risk of treatment failure (RR=0.86, 95% CI=0.22 to 3.30) than those under FB-DOTS. Furthermore, patients who opted for CB-DOTS were less likely to have a positive sputum smear result at the end of the treatment period (p=0.042) compared with their counterparts.

CONCLUSION

The study showed that CB-DOTS is more effective than FB-DOTS in terms of improving cure rate and sputum conversion rate, as well as lowering treatment failure rate. Our findings show the need for scaling up and a further decentralisation of CB-DOTS approach to improve access to TB treatment service for the rural community.

A cohort study analyzing the impact of socioeconomic and spatial characteristics alongside treatment regimens on the environmental-health outcomes of the MDR-TB treatment in Pakistan

This study identifies and analyzes a number of factors that correlate with the environmental-health outcome of multi-drug resistance tuberculosis (MDR-TB) treatment in Pakistan. Survival analysis is carried out by applying the multivariable Cox Proportional Hazard model on secondary data of 369 patients registered at three main MDR-TB sites in Pakistan during 2012-2017. Results show that there is no difference in survival of patients between the two treatment arms, hospital and ambulatory care. Male gender and travel expenditure are found to be negatively associated with the environmental-health outcome, whereas spatial characteristic of time expenditure is positively related to it supporting distance bias approach. Medical expenditure is also positively related to the environmental-health outcome. The study concludes that availability of affordable and accessible health services, better environmental conditions, and ambulatory care based on WHO recommendation as well as health education along with social protection schemes should be ensured by the government to improve environmental-health outcome in the resource-scarce setting in Pakistan.

Challenges in delivery of tuberculosis Services in Ethiopian Pastoralist Settings: clues for reforming service models and organizational structures

Background

The End-TB strategy aims to see a world free of tuberculosis (TB) by the coming decade through detecting and treating all cases irrespective of socioeconomic inequalities. However, case detections and treatment outcomes have not been as they should be in Somali pastoral settings of Ethiopia. Hence, this study aimed to explore the challenges that hinder the delivery and utilization of TB services in pastoral areas.

Methods

A qualitative study was conducted between December 2017 and October 2018 among pastoralist patients with delay of ≥2 months in seeking healthcare, healthcare providers and programme managers. Data were collected from different sources using 41 in-depth interviews, observations of facilities and a review meeting of providers from 50 health facilities. The data were transcribed, coded and analyzed to identify pre-defined and emerging sub-themes. ATLAS.ti version 7.0 was used for coding data, categorizing codes, and visualizing networks.

Results

Poor knowledge of TB and its services, limited accessibility (unreachability, unavailability and unacceptability), pastoralism, and initial healthcare-seeking at informal drug vendors that provide improper medications were the key barriers hindering the uptake of TB medical services. Inadequate infrastructure, shortage of trained and enthused providers, interruptions of drugs and laboratory supplies, scarce equipment, programme management gaps, lack of tailored approach, low private engagement, and cross-border movement were the major challenges affecting the provision of TB services for pastoral communities. The root factors were limited potential healthcare coverage, lack of zonal and district TB units, mobility and drought, strategy and funding gaps, and poor development infrastructure.

Conclusion

In pastoral settings of Ethiopia, the major challenges of TB services are limited access, illicit medication practices, inadequate resources, structural deficits, and lack of tailored approaches. Hence, for the pastoral TB control to be successful, mobile screening and treatment modalities and engaging rural drug vendors will be instrumental in enhancing case findings and treatment compliance; whereas, service expansion and management decentralization will be essential to create responsive structures for overcoming challenges.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06662-3.

Surveillance of tuberculosis and treatment outcomes following screening and therapy interventions among marriage-migrants and labor-migrants from high TB endemic countries in Taiwan

Background

Tuberculosis (TB) among migrants from high-risk countries and underling interventions were concerned for disease control. This study aimed to assess the TB trends among marriage-migrants with the 1–2-round vs. labor-migrants with the four-round TB screenings in the period of the first four post-entry years; pre-entry screenings by an initial chest X-ray (CXR) were conducted during 2012–2015, and a friendly treatment policy was introduced in 2014.

Methods

TB data of migrants during 2012–2015 were obtained from the National TB Registry Database and analyzed. The incidences, clinical characteristics, and treatment outcomes were assessed to explore the impact of underlying interventions.

Results

During post-entry 0–4 years, the TB incidence rates among marriage-migrants ranged 11–90 per 100,000 person-years, with 60.8% bacteria-positive and 28.2% smear-positive cases. Whereas among labor migrants, the incidence rates ranged 67–120 per 100,000 person-years, with 43.6% bacteria-positive and 13.7% smear-positive cases. All migrants originated from Southeast Asia following pre-entry health screening in 2012–2015. The TB cases among marriage-migrants were with a higher proportion of sputum-smear-positivity (SS+) (OR: 4.82, 95% CI [3.7–6.34]) and CXR cavitation (OR: 2.90, 95% CI [2.10–4.01]). Marriage-migrants with TB had treatment completion rate of >90%, which was above the WHO target. For labor-migrants with TB, when compared the period of post- vs. pre-implementation of the friendly therapy policy that eliminated compulsory repatriation, the overall treatment completion rate of those who stayed in Taiwan improved by 30.9% (95% CI [24.3–37.6]) vs. 6.7% (95% CI [3.8–9.7]), which exceeded a 4.88-fold (95% CI: 3.83–6.22) improvement. Additionally, the treatment initiation rate within 30 days of diagnosis for SS- TB and B- TB cases during post- vs. pre-implementation of the therapy policy was increased, that is, 77.1% vs. 70.9% (OR: 1.38, 95% CI [1.12–1.70]) and 78% vs. 77% (OR: 1.64, 95% CI [1.38–1.95]).

Conclusion

Multiple CXR screenings could identify more TB cases with sputum-smear-negativity (SS-) TB at the early-stage, introducing latent tuberculosis infection (LTBI) screening might save underlying efforts. For those labor-migrants with TB who stayed in the receiving country, the friendly TB therapy policy not only significantly improved the treatment completion but also the early treatment initiation.

Identifying geographical heterogeneity of pulmonary tuberculosis in southern Ethiopia: a method to identify clustering for targeted interventions

Background

Previous studies from Ethiopia detected disease clustering using broader geographic settings, but limited information exists on the spatial distribution of the disease using residential locations. An assessment of predictors of spatial variations of TB at community level could fill the knowledge gaps, and helps in devising tailored interventions to improve TB control.

Objective

To assess the pattern of spatial distribution of pulmonary tuberculosis (PTB) based on geographic locations of individual cases in the Dale district and Yirga Alem town in southern Ethiopia.

Methods

The socio-demographic characteristics of PTB cases were collected using a structured questionnaire, and spatial information was collected using geographic position systems. We carried out Getis and Ord (Gi*) statistics and scan statistics to explore the pattern of spatial clusters of PTB cases, and geographically weighted regression (GWR) was used to assess the spatial heterogeneities in relationship between predictor variables and PTB case notification rates (CNRs).

Results

The distribution of PTB varied by enumeration areas within the kebeles, and we identified areas with significant hotspots in various areas ineach year. In GWR analysis, the disease distribution showed a geographic heterogeneity (non-stationarity) in relation to physical access (distance to TB control facilities) and population density (AICc = 5591, R² = 0.3359, adjusted R² = 0.2671). The model explained 27% of the variability in PTB CNRs (local R² ranged from 0.0002–0.4248 between enumeration areas). The GWR analysis showed that areas with high PTB CNRs had better physical accessibility to TB control facilities and high population density. The effect of physical access on PTB CNRs changed after the coverage of TB control facilities was improved.

Conclusion

We report a varying distribution of PTB in small and different areas over 10 years. Spatial and temporal analysis of disease distribution can be used to identify areas with a high burden of disease and predictors of clustering, which helps in making policy decisions and devising targeted interventions.

HIV infection modifies the relationship between distance to a health facility and treatment success rate for tuberculosis in rural eastern Uganda

•

Distance from residence to a health facility presents a physical barrier.

•

Our data show that long-distance is associated with a lower treatment success rate.

•

Also, we found long-distance is insignificantly associated with high mortality.

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HIV modifies the effect of long-distance on mortality.

•

People with tuberculosis who travel long distances need improved access to treatment.

Rationale

Distance from residence to a health facility especially in rural areas presents a physical barrier and may influence tuberculosis (TB) treatment outcomes.

Objectives

We examined the association between distance from residence to a health facility and TB treatment outcomes namely treatment success rate (TSR) and mortality, and whether HIV influences this relationship among people with TB in Kumi district in rural eastern Uganda.

Methods

In this cross-sectional design, we abstracted data from TB unit registers across four large health facilities. Travel of ≥5 km to a health facility was considered a long distance. The primary outcome was TSR and the secondary was mortality. We performed a generalized linear model with Poisson distribution with a log-link and robust standard errors to determine the association between distance and the study outcomes adjusting for potential confounders. We report the adjusted risk ratio (aRR) and 95% confidence interval (CI).

Measurement and results

Of 611 participants studied, 484 (79.2%) were successfully treated, 18 (2.9%) died, and 359 (58.7%) travelled a long distance to access TB treatment. Long-distance was significantly associated with lower TSR (aRR, 0.93; 95% CI, 0.89–0.96). Further analysis showed that longer distance was associated with lower TSR among HIV positive persons with TB (aRR, 0.83; 95% CI, 0.72–0.96), but not among HIV negative persons with TB (aRR, 0.94; 95% CI, 0.85–1.03). Although it was not significant, longer distance showed a tendency towards worse mortality among HIV positive people with TB (aRR, 2.78; 95% CI, 0.80–9.66), but not among HIV negative people with HIV (aRR, 0.21; 0.03–1.74).

Conclusions

A majority of people with TB travel long distances to access treatment. Long distances are associated with lower TSR and higher mortality and affect people with TB who are HIV positive but not HIV negative. Interventions should focus on improving access to treatment for people with TB who travel long distances.

Spatial-temporal clustering of notified pulmonary tuberculosis and its predictors in East Gojjam Zone, Northwest Ethiopia

BACKGROUND

Tuberculosis (TB) remains a key health menace in Ethiopia and its districts. This study aimed to assess the spatial-temporal clustering of notified pulmonary TB (PTB) cases in East Gojjam Zone, Northwest Ethiopia.

METHODS

A retrospective study was conducted among all PTB cases reported from 2013-2019. Case notification rates (CNRs) of PTB cases at Kebele (the lowest administrative unit), woreda, and zone levels were estimated. The PTB clustering was done using global Moran's I statistics on Arc GIS 10.6. We used Kulldorff SaTScan 9.6 with a discrete Poisson model to identify statistically significant spatial-temporal clustering of PTB cases at Kebele level. Similarly, a negative binomial regression analysis was used to identify factors associated with the incidence of PTB cases at kebele level.

RESULTS

A total of 5340 (52%) smear-positive and 4928 (48%) smear-negative PTB cases were analyzed. The overall mean CNR of PTB cases at zone, woreda and Kebele levels were 58(47-69), 82(56-204), and 69(36-347) per 100,000 population, respectively. The purely spatial cluster analysis identified eight most likely clusters (one for overall and one per year for seven reporting years) and 47 secondary clusters. Similarly, the space-time scan analysis identified one most likely and seven secondary clusters. The purely temporal analysis also detected one most likely cluster from 2013-2015. Rural residence, distance from the nearest health facility, and poor TB service readiness were factors (p-value <0.05) to PTB incidence at kebele level.

CONCLUSION

The distribution of PTB cases was clustered. The PTB CNR was low and showed a decreasing trend during the reporting periods. Rural residence, distance from the health facilities, and poor facility readiness were factors of PTB incidence. Improving accessibility and readiness of health facilities mainly to rural and hotspot areas is vital to increase case detection and reduce TB transmission.

Predictors of smear non-conversion among new-treatment pulmonary tuberculosis: a single center case-control study in Indonesia

BACKGROUND Previous studies concluded predictors of smear non-conversion pulmonary tuberculosis (TB) globally as well as in Indonesia. However, there is a limited data in hospital setting. This study aimed to explore predictors of smear non-conversion pulmonary TB in hospital setting. METHODS A case-control study was conducted to explore predictors of smear nonconversion among new-treatment pulmonary TB in Dr. Kariadi General Hospital from 2017 to 2019. Number of cases and controls have been determined consecutively. Data were collected from secondary data accessed in medical records and directly from subjects. Non-conversion status in the case group was defined as a persistent sputum smear-positive after 2 months of intensive phase of treatment. The subjects’ characteristics i.e., age, sex, BMI, education level, occupational status, and predictors of smear non-conversion, i.e., patient’s compliance, smoking status, alcohol consumption, presence of drugs side effects, health care access, first acid-fast bacilli (AFB) smear grading, diabetes mellitus (DM), housing condition, housing density, and household income were observed. Chi-square test and binary logistic regression were used. RESULTS 35 subjects were determined in the case group while 76 subjects were the control group and involved in the final analysis. Age, sex, first AFB smear grading, smoking status, housing condition, housing density, and DM were involved in the model of logistic regression. DM (OR = 3.4; 95% CI = 1.19–10.00) and first AFB smear grading (OR = 11.2; 95% CI = 3.86–33.00) were concluded as the predictors of smear nonconversion. CONCLUSIONS DM and first AFB smear grading were the predictors of smear nonconversion among new-treatment pulmonary TB subjects.

Bayesian Spatial Survival Analysis of Duration to Cure among New Smear-Positive Pulmonary Tuberculosis (PTB) Patients in Iran, during 2011-2018

Mycobacterium tuberculosis is the causative agent of tuberculosis (TB), and pulmonary TB is the most prevalent form of the disease worldwide. One of the most concrete actions to ensure an effective TB control program is monitoring TB treatment outcomes, particularly duration to cure; but, there is no strong evidence in this respect. Thus, the primary aim of this study was to examine the possible spatial variations of duration to cure and its associated factors in Iran using the Bayesian spatial survival model. All new smear-positive PTB patients have diagnosed from March 2011 to March 2018 were included in the study. Out of 34,744 patients, 27,752 (79.90%) patients cured and 6992 (20.10%) cases were censored. For inferential purposes, the Markov chain Monte Carlo algorithms are applied in a Bayesian framework. According to the Bayesian estimates of the regression parameters in the proposed model, a Bayesian spatial log-logistic model, the variables gender (male vs. female, TR = 1.09), altitude (>750 m vs. ≤750 m, TR = 1.05), bacilli density in initial smear (3+ and 2+ vs. 1–9 Basil & 1+, TR = 1.09 and TR = 1.02, respectively), delayed diagnosis (>3 months vs. <1 month, TR = 1.02), nationality (Iranian vs. other, TR = 1.02), and location (urban vs. rural, TR = 1.02) had a significant influence on prolonging the duration to cure. Indeed, pretreatment weight (TR = 0.99) was substantially associated with shorter duration to cure. In summary, the spatial log-logistic model with convolution prior represented a better performance to analyze the duration to cure of PTB patients. Also, our results provide valuable information on critical determinants of duration to cure. Prolonged duration to cure was observed in provinces with low TB incidence and high average altitude as well. Accordingly, it is essential to pay a special attention to such provinces and monitor them carefully to reduce the duration to cure while maintaining a focus on high-risk provinces in terms of TB prevalence.

Geographical access to point-of-care testing for hypertensive disorders of pregnancy as an integral part of maternal healthcare in Ghana

Background

Hypertensive disorders of pregnancy (HDP) are associated with high maternal mortality in Ghana and globally. Evidence shows that there is poor availability of pregnancy-related point-of-care (POC) tests in Ghana’s primary healthcare (PHC) clinics (health centre or community-based health planning services facilities). Therefore, we employed geographic information systems to estimate the geographical distribution of and physical accessibility to HDP POC testing services in the Upper East Region (UER), Ghana.

Methods

We collected data on 100 out of 365 PHC clinics, public hospitals providing HDP testing, PHC clinic type, ownership, and availability of urine dipsticks and blood pressure (BP) devices. We also obtained the geo-located data of the PHC clinics and hospitals using the global positioning system. We employed ArcGIS 10.4 to measure the distance and travel time from the location of each PHC clinic without HDP POC testing services as well as from all locations of each district to the nearest hospital/clinic where the service is available. The travel time was estimated using an assumed motorised tricycle speed of 20 km/hour. We further calculated the spatial distribution of the hospitals/clinics providing HDP POC testing services using the spatial autocorrelation tool in ArcMap, and Stata version 14 for descriptive statistical analysis.

Results

Of the 100 participating PHC clinics, POC testing for HDP was available in 19% (14% health centres and 5% community-based health planning services compounds) in addition to the 10 hospitals use as referral points for the service. The findings indicated that the spatial pattern of the distribution of the health facilities providing HDP POC testing was random (z-score = -0.61; p = 0.54). About 17% of the PHC clinics without HDP POC testing service were located > 10 km to the nearest facility offering the service. The mean distance and travel time from PHC clinics without HDP POC testing to a health facility providing the service were 11.4 ± 9.9 km and 31.1 ± 29.2 min respectively. The results suggest that if every 19% of the 365 PHC clinics are offering HDP POC testing in addition to these 10 hospitals identified, then the estimated coverage (health facility-to-women in fertility age ratio) in the UER is 1: 3,869.

Conclusions

There is poor physical accessibility to HDP POC testing services from PHC clinics without HDP POC testing in the UER. Mothers who obtain maternal healthcare in about 17% of the PHC clinics travel long distances (> 10 km) to access the service when needed. Hence, there is a need to improve the availability of HDP POC diagnostic tests in Ghana’s rural clinics.

Finding gaps in TB notifications: spatial analysis of geographical patterns of TB notifications, associations with TB program efforts and social determinants of TB risk in Bangladesh, Nepal and Pakistan

BACKGROUND

In order to effectively combat Tuberculosis, resources to diagnose and treat TB should be allocated effectively to the areas and population that need them. Although a wealth of subnational data on TB is routinely collected to support local planning, it is often underutilized. Therefore, this study uses spatial analytical techniques and profiling to understand and identify factors underlying spatial variation in TB case notification rates (CNR) in Bangladesh, Nepal and Pakistan for better TB program planning.

METHODS

Spatial analytical techniques and profiling was used to identify subnational patterns of TB CNRs at the district level in Bangladesh (N = 64, 2015), Nepal (N = 75, 2014) and Pakistan (N = 142, 2015). A multivariable linear regression analysis was performed to assess the association between subnational CNR and demographic and health indicators associated with TB burden and indicators of TB programme efforts. To correct for spatial dependencies of the observations, the residuals of the multivariable models were tested for unexplained spatial autocorrelation. Spatial autocorrelation among the residuals was adjusted for by fitting a simultaneous autoregressive model (SAR).

RESULTS

Spatial clustering of TB CNRs was observed in all three countries. In Bangladesh, TB CNR were found significantly associated with testing rate (0.06%, p < 0.001), test positivity rate (14.44%, p < 0.001), proportion of bacteriologically confirmed cases (- 1.33%, p < 0.001) and population density (4.5*10-3%, p < 0.01). In Nepal, TB CNR were associated with population sex ratio (1.54%, p < 0.01), facility density (- 0.19%, p < 0.05) and treatment success rate (- 3.68%, p < 0.001). Finally, TB CNR in Pakistan were found significantly associated with testing rate (0.08%, p < 0.001), positivity rate (4.29, p < 0.001), proportion of bacteriologically confirmed cases (- 1.45, p < 0.001), vaccination coverage (1.17%, p < 0.001) and facility density (20.41%, p < 0.001).

CONCLUSION

Subnational TB CNRs are more likely reflective of TB programme efforts and access to healthcare than TB burden. TB CNRs are better used for monitoring and evaluation of TB control efforts than the TB epidemic. Using spatial analytical techniques and profiling can help identify areas where TB is underreported. Applying these techniques routinely in the surveillance facilitates the use of TB CNRs in program planning.

Spatial distribution of people diagnosed with tuberculosis through routine and active case finding: a community-based study in Kampala, Uganda

BACKGROUND

Routine tuberculosis (TB) notifications are geographically heterogeneous, but their utility in predicting the location of undiagnosed TB cases is unclear. We aimed to identify small-scale geographic areas with high TB notification rates based on routinely collected data and to evaluate whether these areas have a correspondingly high rate of undiagnosed prevalent TB.

METHODS

We used routinely collected data to identify geographic areas with high TB notification rates and evaluated the extent to which these areas correlated with the location of undiagnosed cases during a subsequent community-wide active case finding intervention in Kampala, Uganda. We first enrolled all adults who lived within 35 contiguous zones and were diagnosed through routine care at four local TB Diagnosis and Treatment Units. We calculated average monthly TB notification rates in each zone and defined geographic areas of "high risk" as zones that constituted the 20% of the population with highest notification rates. We compared the observed proportion of TB notifications among residents of these high-risk zones to the expected proportion, using simulated estimates based on population size and random variation alone. We then evaluated the extent to which these high-risk zones identified areas with high burdens of undiagnosed TB during a subsequent community-based active case finding campaign using a chi-square test.

RESULTS

We enrolled 45 adults diagnosed with TB through routine practices and who lived within the study area (estimated population of 49 527). Eighteen zones reported no TB cases in the 9-month period; among the remaining zones, monthly TB notification rates ranged from 3.9 to 39.4 per 100 000 population. The five zones with the highest notification rates constituted 62% (95% CI: 47-75%) of TB cases and 22% of the population-significantly higher than would be expected if population size and random chance were the only determinants of zone-to-zone variation (48%, 95% simulation interval: 40-59%). These five high-risk zones accounted for 42% (95% CI: 34-51%) of the 128 cases detected during the subsequent community-based case finding intervention, which was significantly higher than the 22% expected by chance (P < 0.001) but lower than the 62% of cases notified from those zones during the pre-intervention period (P = 0.02).

CONCLUSIONS

There is substantial heterogeneity in routine TB notification rates at the zone level. Using facility-based TB notification rates to prioritize high-yield areas for active case finding could double the yield of such case-finding interventions.

Low Tuberculosis (TB) Case Detection: A Health Facility-Based Study of Possible Obstacles in Kaffa Zone, Southwest District of Ethiopia

Background

In Ethiopia, the national TB case detection rate is becoming improved; still some districts are not able to meet their case detection targets which leads to ongoing spread of TB infections to family members and communities. This study was intended to assess possible obstacles contributing to low TB case detection in Kaffa zone, Southwest Ethiopia.

Methods

A cross-sectional descriptive study involving qualitative and quantitative data was conducted from Mar. to Sep. 2019. Sociodemographic characteristics and data on duration of cough, whether sputum smear microscopy was requested or not, and data on TB knowledge and health care-seeking practice were collected from outpatients. Health care delivery barrier for TB case detection was also explored by using in-depth interview and FGD of health staff.

Results

From 802 outpatients with coughing for 2 or more weeks of duration, 334 (41.6%) of them were not requested to have TB microscopic diagnosis. Of these, 11/324 (3.4%) of them were positive for TB after sputum smear microscopy. Only 24.2% of the outpatients were aware as they have had health education on TB disease. Twenty-eight percent of patients perceived that TB was due to exposure to cold air, and 13.5% could not mention any sign or symptom of TB. Amazingly, 54.2% of them did not have any information as current TB diagnosis and treatment is free. Thirty-five percent of the patients were taking antibiotics before visiting the health facility. The interrupted supply of TB diagnostic reagents, frequent electricity interruption, shortage of trained TB care providers, weak health information system, and weak active case finding practice were explored as the factors contributing to low TB case detection.

Conclusion

Interrupted functioning of diagnostic centers, shortage of trained care providers, limited active TB case finding practice, weak health information system, and inadequate knowledge and health care-seeking practice of the patients were identified as contributors for low TB case detection. Thus, improving functioning of diagnostic centers, active TB case finding activities, and expanding health education on TB disease will help to improve TB case detection in the districts.

Geographical Accessibility to Glucose-6-Phosphate Dioxygenase Deficiency Point-of-Care Testing for Antenatal Care in Ghana

Background: Glucose-6-Phosphate Dehydrogenase (G6PD) deficiency screening test is essential for malaria treatment, control, and elimination programs. G6PD deficient individuals are at high risk of severe hemolysis when given anti-malarial drugs such as primaquine, quinine, other sulphonamide-containing medicines, and chloroquine, which has recently been shown to be potent for the treatment of coronavirus disease (COVID-19). We evaluated the geographical accessibility to POC testing for G6PD deficiency in Ghana, a malaria-endemic country. Methods: We obtained the geographic information of 100 randomly sampled clinics previously included in a cross-sectional survey. We also obtained the geolocated data of all public hospitals providing G6PD deficiency testing services in the region. Using ArcGIS 10.5, we quantified geographical access to G6PD deficiency screening test and identified clinics as well as visualize locations with poor access for targeted improvement. The travel time was estimated using an assumed speed of 20 km per hour. Findings: Of the 100 clinics, 58% were Community-based Health Planning and Services facilities, and 42% were sub-district health centers. The majority (92%) were Ghana Health Service facilities, and the remaining 8% were Christian Health Association of Ghana facilities. Access to G6PD deficiency screening test was varied across the districts, and G6PD deficiency screening test was available in all eight public hospitals. This implies that the health facility-to-population ratio for G6PD deficiency testing service was approximately 1:159,210 (8/1,273,677) population. The spatial analysis quantified the current mean distance to a G6PD deficiency testing service from all locations in the region to be 34 ± 14 km, and travel time (68 ± 27 min). The estimated mean distance from a clinic to a district hospital for G6PD deficiency testing services was 15 ± 11 km, and travel time (46 ± 33 min). Conclusion: Access to POC testing for G6PD deficiency in Ghana was poor. Given the challenges associated with G6PD deficiency, it would be essential to improve access to G6PD deficiency POC testing to facilitate administration of sulphadoxine-pyrimethamine to pregnant women, full implementation of the malaria control program in Ghana, and treatment of COVID-19 patients with chloroquine in malaria-endemic countries. To enable the World Health Organization include appropriate G6PD POC diagnostic tests in its list of essential in-vitro diagnostics for use in resource-limited settings, we recommend a wider evaluation of available POC diagnostic tests for G6PD deficiency, particularly in malaria-endemic countries.

Does time to loss to follow-up differ among adult tuberculosis patients initiated on tuberculosis treatment and care between general hospital and health centers? A retrospective cohort study

BACKGROUND

Patients' loss to follow-up (LTFU) from tuberculosis treatment and care is a growing worry in Ethiopia. But, available information is inadequate in assessing the time to tuberculosis patient loss to follow-up difference between health centers and a general hospital in Ethiopia. We aimed to assess time to LTFU difference between health centers and a general hospital in rural Ethiopia.

METHODS

We conducted a retrospective cohort study from September 2008 to August 2015 and collected data from September 1 to October 02, 2016. A total of 1341 TB patients with known treatment outcomes were included into the study. Log rank test was used to compare the difference in time to TB patient loss to follow-up between health centers and a general hospital, whereas Cox proportional hazard model was used to assess factors associated with time to loss to follow-up in both settings.

RESULTS

We reviewed a total of 1341 patient records, and the overall follow-up time was 3074.7 and 3974 person months of observation (PMOs) for TB patients followed at health centers and a general hospital, respectively. The incidence of loss to follow-up rate was 27.3 per 1000 PMOs and 9.6 per 1000 PMOs, at health centers and a general hospital, respectively. From the overall loss to follow-ups that occurred, 55 (65.5%) and 33 (86.8%) of LTFUs occurred during the intensive phase and grew to 78 (92.9%) and 38 (100%) at health center and a general hospital, respectively, at the end of 6-month observation period. Older age (AOR = 1.7, 95%CI, 1.2-2.5, P < 0.001), being a rural resident (AHR = 2.7, 95%CI, 1.6-4.6), HIV reactive (AHR = 2.2, 95%CI, 1.5-3.2), following treatment and care in health center (AHR = 3.38, 95%CI, 2.06-5.53), and living at more than 10 km away from the health facility (AHR = 3.4, 95%CI, 2.1-5.7) were predictors for time to loss to follow-up among TB patients on treatment and care.

CONCLUSION

Time to TB patient loss to follow-up between health centers and a general hospital was significant. Loss to follow-up was high in patients with older age, rural residence, sero positive for HIV, living further from the health facilities, and following treatment and care at health centers. Strengthening the DOTs program with special emphasis on health centers is highly recommended.

Barriers for tuberculosis case finding in Southwest Ethiopia: A qualitative study

BACKGROUND

Ethiopia is one of the countries with a high burden of tuberculosis (TB). Jimma Zone has the lowest TB case notification rate compared to the national and World Health Organization's (WHO) targets. The aim of the present study was to identify barriers, and explore the origin of these barriers in relation to TB case finding.

METHODS

A qualitative study was conducted by using different data collection methods and sources. Sixty in-depth interviews with TB treatment providers, program managers and TB patients were included. In addition, 42 governmental health facilities were observed for availability of resources. Data obtained from the in-depth interviews were transcribed, coded, categorized and thematized. Atlas.ti version 7.1 software was used for the data coding and categorizing.

RESULTS

Inadequate resources for TB case finding, such as a shortage of health-care providers, inadequate basic infrastructure, and inadequate diagnostic equipment and supplies, as well as limited access to TB diagnostic services such as an absence of nearby health facilities providing TB diagnostic services and health system delays in the diagnostic process, were identified as barriers for TB case finding. We identified the absence of trained laboratory professionals in 11, the absence of clean water supply in 13 and the electricity in seven health facilities. Furthermore, we found that difficult topography, the absence of proper roads, an inadequate collaboration with other sectors (such as education), a turnover of laboratory professionals, and a low community mobilization, as the origin of some of these barriers.

CONCLUSION

Inadequate resources for TB case finding, and a limited access to diagnostic services, were major challenges affecting TB case finding. The optimal application of the directly observed treatment short course (Stop TB) strategy is crucial to increase the current low TB case notification rate. Practical strategies need to be designed to attract and retain health professionals in the health system.

Spatial distribution of tuberculosis in a rural region of Western Province, Papua New Guinea

Introduction

There is a high burden of tuberculosis (TB) in the Western Province, Papua New Guinea. This study aims to describe the spatial distribution of TB in the Balimo District Hospital (BDH) catchment area to identify TB patient clusters and factors associated with high rates of TB.

Methods

Information about TB patients was obtained from the BDH TB patient register for the period 26 April 2013 to 25 February 2017. The locations of TB patients were mapped, and the spatial scan statistic was used to identify high- and low-rate TB clusters in the BDH catchment area.

Results

A total of 1568 patients were mapped with most being from the Balimo Urban (n = 252), Gogodala Rural (n = 1010) and Bamu Rural (n = 295) local level government (LLG) areas. In the Gogodala region (Balimo Urban and Gogodala Rural LLGs), high-rate clusters occurred closer to the town of Balimo, while low-rate clusters were located in more remote regions. In addition, closer proximity to Balimo was a predictor of high-rate clustering.

Discussion

There is heterogeneity in the distribution of TB in the Balimo region. Active case-finding activities indicated potential underdiagnosis of TB and the possibility of associated missed diagnoses of TB. The large BDH catchment area emphasizes the importance of the hospital in managing TB in this rural region.

Estimating the Spatial Accessibility to Blood Group and Rhesus Type Point-of-Care Testing for Maternal Healthcare in Ghana

Background: In Ghana, a blood group and rhesus type test is one of the essential recommended screening tests for women during antenatal care since blood transfusion is a key intervention for haemorrhage. We estimated the spatial accessibility to health facilities for blood group and type point-of-care (POC) testing in the Upper East Region (UER), Ghana. Methods: We assembled the attributes and spatial data of hospitals, clinics, and medical laboratories providing blood group and rhesus type POC testing in the UER. We also obtained the spatial data of all the 131 towns, and 94 health centres and community-based health planning and services (CHPS) compounds providing maternal healthcare in the region. We further obtained the topographical data of the region, and travel time estimated using an assumed tricycle speed of 20 km/h. We employed ArcGIS 10.5 to estimate the distance and travel time and locations with poor spatial access identified for priority improvement. Findings: In all, blood group and rhesus type POC testing was available in 18 health facilities comprising eight public hospitals and six health centres, one private hospital, and three medical laboratories used as referral points by neighbouring health centres and CHPS compounds without the service. Of the 94 health centres and CHPS compounds, 51.1% (48/94) and 66.4% (87/131) of the towns were within a 10 km range to a facility providing blood group and rhesus type testing service. The estimated mean distance to a health facility for blood group and rhesus POC testing was 8.9 ± 4.1 km, whilst the mean travel time was 17.8 ± 8.3 min. Builsa South district recorded the longest mean distance (25.6 ± 7.4 km), whilst Bongo district recorded the shortest (3.1 ± 1.9 km). The spatial autocorrelation results showed the health facilities providing blood group and rhesus type POC testing were randomly distributed in the region (Moran Index = 0.29; z-score = 1.37; p = 0.17). Conclusion: This study enabled the identification of district variations in spatial accessibility to blood group and rhesus type POC testing in the region for policy decisions. We urge the health authorities in Ghana to evaluate and implement recommended POC tests such as slide agglutination tests for blood group and rhesus type testing in resource-limited settings.

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.

Use of Geographically Weighted Poisson Regression to examine the effect of distance on Tuberculosis incidence: A case study in Nam Dinh, Vietnam

Objectives

This study aimed to examine the potential of combining routine tuberculosis (TB) surveillance and demographic and socioeconomic variables into the Geographic Information System (GIS) to describe the geographical distribution of TB notified incidence in relation to distances to health services as well as local demographic and socioeconomic factors, including population density, urban/rural status, and household poverty rates in Nam Dinh, Vietnam. It also aimed to compare the conventional Generalized Linear Models (GLM) Poisson regression model and Geographically Weighted Poisson Regression (GWPR) models in order to determine the best fitting model that can be used to investigate the relationship between TB notified incidence and distances and the social risk factors.

Methods

The data of new and relapse patients with all forms of TB aged ≥15 years residing in Nam Dinh (Vietnam) from 2012 to 2015 were collected from the Administration of Medical Services’ (Ministry of Health of Vietnam) TB surveillance database. Data on the population and household poverty rates from 2012 to 2015 were gathered from the Nam Dinh Statistical Office. Distances between communes and the nearest TB diagnostic facilities in districts were computed. The TB notified incidence per 100,000 population was denoted by indirect age and sex standardized incidence ratio. GLM Poisson regression and GWPR were performed to assess the relationship between distance and TB incidence.

Results

The average notified TB incidence level measured from 2012 to 2015 is 82 per 100,000 population (range: 79-84/100,000). The distance to the nearest TB diagnosis presents a negative effect on TB notified incidence. By capturing spatial heterogeneity, the GWPR may be better at fitting data (corrected Aikake information criterion [AICc] = 245.71, residual deviance = 221.12) than the traditional GLM (AICc = 251.53, residual deviance = 241.21)

Conclusions

GIS technologies benefit TB surveillance system. Distances should be considered when planning methods of improving access for those who live far from TB diagnostic services, thereby improving TB detection. Additional studies must confirm the association between geographic distance and TB case detection and must explore other factors that may affect TB notified incidence.

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.

Estimating the spatial risk of tuberculosis distribution in Gurage zone, southern Ethiopia: a geostatistical kriging approach

Background

In low-income countries it is difficult to obtain complete data that show spatial heterogeneity in the risk of tuberculosis within-and-between smaller administrative units. This may contribute to the partial effectiveness of tuberculosis control programs. The aim of this study was to estimate the spatial risk of tuberculosis distribution in Gurage Zone, Southern Ethiopia using limited spatial datasets.

Methods

A total of 1601 patient data that were retrieved from unit tuberculosis registers were included in the final analyses. The population and geo-location data were obtained from the Central Statistical Agency of Ethiopia. Altitude data were extracted from ASTER Global Digital Elevation Model Version 2. Aggregated datasets from sample of 169(40%), 254(60%) and 338(80%) kebeles were used to estimate the spatial risk of TB distribution in the Gurage Zone by using a geostatistical kriging approach. The best set of input parameters were decided based on the lowest prediction error criteria of the cross-validation technique. ArcGIS 10.2 was used for the spatial data analyses.

Results

The best semivariogram models were the Pentaspherical, Rational Quadratic, and K-Bessel for the 40, 60 and 80% spatial datasets, respectively. The predictive accuracies of the models have improved with the true anisotropy, altitude and latitude covariates, the change in detrending pattern from local to global, and the increase in size of spatial dataset. The risk of tuberculosis was estimated to be higher at western, northwest, southwest and southeast parts of the study area, and crossed between high and low at west-central parts.

Conclusion

This study has underlined that the geostatistical kriging approach can be applied to estimate the spatial risk of tuberculosis distribution in data limited settings. The estimation results may help local public health authorities measure burden of the disease at all locations, identify geographical areas that require more attention, and evaluate the impacts of intervention programs.

Electronic supplementary material

The online version of this article (10.1186/s12889-018-5711-3) contains supplementary material, which is available to authorized users.

Spatial and space-time clustering of tuberculosis in Gurage Zone, Southern Ethiopia

INTRODUCTION

Spatial targeting is advocated as an effective method that contributes for achieving tuberculosis control in high-burden countries. However, there is a paucity of studies clarifying the spatial nature of the disease in these countries. This study aims to identify the location, size and risk of purely spatial and space-time clusters for high occurrence of tuberculosis in Gurage Zone, Southern Ethiopia during 2007 to 2016.

MATERIALS AND METHODS

A total of 15,805 patient data that were retrieved from unit TB registers were included in the final analyses. The spatial and space-time cluster analyses were performed using the global Moran's I, Getis-Ord [Formula: see text] and Kulldorff's scan statistics.

RESULTS

Eleven purely spatial and three space-time clusters were detected (P <0.001).The clusters were concentrated in border areas of the Gurage Zone. There were considerable spatial variations in the risk of tuberculosis by year during the study period.

CONCLUSIONS

This study showed that tuberculosis clusters were mainly concentrated at border areas of the Gurage Zone during the study period, suggesting that there has been sustained transmission of the disease within these locations. The findings may help intensify the implementation of tuberculosis control activities in these locations. Further study is warranted to explore the roles of various ecological factors on the observed spatial distribution of tuberculosis.

Long-term outcome of smear-positive tuberculosis patients after initiation and completion of treatment: A ten-year retrospective cohort study

BACKGROUND

The status of tuberculosis (TB) patients since initiation of treatment is unknown in South Ethiopia. The objective of this study was to assess the long-term outcomes of smear-positive TB patients since initiation and completion of treatment, which includes TB recurrence and mortality of TB patients.

METHODS

We did a retrospective cohort study on 2,272 smear-positive TB patients who initiated treatment for TB from September 1, 2002-October 10, 2012 in health facilities in Dale district and Yirgalem town administration. We followed them from the date of start of treatment to either the date of interview or date of death.

RESULTS

Recurrence rate of TB was 15.2 per 1000 person-years. Recurrence was higher for re-treatment cases (adjusted hazard ratio (aHR), 2.7; 95% CI, 1.4-5.3). Mortality rate of TB patients was 27.1 per 1,000 person-years. The risk was high for patients above 34 years of age (aHR, 2.1; 95% CI, 1.2-3.9), poor patients (aHR, 1.3; 95% CI, 1.0-1.8), patients with poor treatment outcomes (aHR, 6.7; 95% CI, 5.1-8.9) and for patients treated at least 3 times (aHR 4.8; 95% CI, 2.1-11.1). The excess mortality occurred among patients aged above 34 years was high (41.2/1000 person years).

CONCLUSION

High TB recurrence and death of TB patients was observed among our study participants. Follow-up of TB patients with the risk factors and managing them could reduce the TB burden.

Factors affecting tuberculosis case detection in Kersa District, South West Ethiopia

BACKGROUND

Tuberculosis is one of the deadly communicable diseases which claim the lives of millions in the world. Early case detection and prompt treatment cures the patients, breaks the transmission and improves the control program.

OBJECTIVE

The aim of this study was to investigate the factors affecting tuberculosis case detection in Kersa District, south west Ethiopia.

METHOD

Facility based cross sectional study design was employed in four directly observed treatment short course service providing public health centers. Three hundred eighty four patient folders were reviewed. In-depth interviews was conducted with 18 health care workers including heads of health centers, tuberculosis focal persons, clinicians, laboratory technicians, tuberculosis program coordinator and head of health office.

RESULT

Significant number, 135(35.2%) of tuberculosis suspects were not requested for microscopic examination of sputum smear, the laboratory results 21(8.4%) of requested patients were not recorded in both patient folders and laboratory registers. Only 10 (4.4%) of those examined and recorded were smearing positive. Participants described that the shortage and irregular supply of acid fast bacilli reagents and consumable, inadequate infrastructures, frequent electricity interruption, shortage of trained care providers, negligence of care providers, weakness of laboratory quality assurance system and poor health information use culture were major factors for low case identification.

CONCLUSION

The resource shortage, electricity interruption, low commitment of care providers, weak quality assurance practice and poor health information use culture were major factors for low tuberculosis case identification and should be considered.