Sociodemographic profiling of tuberculosis hotspots in Ethiopia, 2014-2017

Ecological-level factors associated with tuberculosis incidence and mortality: A systematic review and meta-analysis

Globally, tuberculosis (TB) is the leading infectious cause of morbidity and mortality, with the risk of infection affected by both individual and ecological-level factors. While systematic reviews on individual-level factors exist, there are currently limited studies examining ecological-level factors associated with TB incidence and mortality. This study was conducted to identify ecological factors associated with TB incidence and mortality. A systematic search for analytical studies reporting ecological factors associated with TB incidence or mortality was conducted across electronic databases such as PubMed, Embase, Scopus, and Web of Science, from each database's inception to October 30, 2023. A narrative synthesis of evidence on factors associated with TB incidence and mortality from all included studies, alongside random-effects meta-analysis where applicable, estimated the effects of each factor on TB incidence. A total of 52 articles were included in the analysis, and one study analysed two outcomes, giving 53 studies. Narrative synthesis revealed predominantly positive associations between TB incidence and factors such as temperature (10/18 studies), precipitation (4/6), nitrogen dioxide (6/9), poverty (4/4), immigrant population (3/4), urban population (3/8), and male population (2/4). Conversely, air pressure (3/5), sunshine duration (3/8), altitude (2/4), gross domestic product (4/9), wealth index (2/8), and TB treatment success rate (2/2) mostly showed negative associations. Particulate matter (1/1), social deprivation (1/1), and population density (1/1) were positively associated with TB mortality, while household income (2/2) exhibited a negative association. In the meta-analysis, higher relative humidity (%) (relative risk (RR) = 1.45, 95%CI:1.12, 1.77), greater rainfall (mm) (RR = 1.56, 95%CI: 1.11, 2.02), elevated sulphur dioxide (μg m-3) (RR = 1.04, 95% CI:1.01, 1.08), increased fine particulate matter concentration (PM2.5) (μg/ m3) (RR = 1.33, 95% CI: 1.18, 1.49), and higher population density (people/km2) (RR = 1.01,95%CI:1.01-1.02) were associated with increased TB incidence. Conversely, higher average wind speed (m/s) (RR = 0.89, 95%CI: 0.82,0.96) was associated with decreased TB incidence. TB incidence and mortality rates were significantly associated with various climatic, socioeconomic, and air quality-related factors. Intersectoral collaboration across health, environment, housing, social welfare and economic sectors is imperative for developing integrated approaches that address the risk factors associated with TB incidence and mortality.

Spatio-temporal patterns of dengue in Bangladesh during 2019 to 2023: Implications for targeted control strategies

BACKGROUND

Dengue, a viral infection transmitted by Aedes species mosquitoes, presents a substantial global public health concern, particularly in tropical regions. In Bangladesh, where dengue prevalence is noteworthy, accurately mapping the distribution of high-risk and low-risk areas and comprehending the clustering of dengue cases throughout the year is essential for the development of effective risk-based prevention and control strategies. Our objective was to identify dengue hotspots and temporal patterns over the years across Bangladesh in the years 2019-2023 excluding year 2020.

METHODS

A sequential spatial analysis was employed for each year to identify high-risk areas for dengue cases. Choropleth graphs were used to visualize the geographic distribution of dengue incidence rates per million population across the areas. Monthly distribution analysis was performed to identify temporal trends over the year 2022 and 2023. Additionally, the global Moran's I test was used to assess the overall geographical pattern. Subsequently, Anselin local Moran's I test was employed to identified clustering and hotspots of dengue incidences.

RESULTS

Dengue cases in Bangladesh exhibited a significant increase from 2019 to 2023 (excluding 2020 data), with a cumulative total of 513,344 reported cases. Dhaka city initially bore substantial burden, accounting for over half (51%) of the 101,354 cases in 2019. The case fatality rate also demonstrated a steadily rise, reaching 0.5% in 2023 with 321,179 cases (a five-fold increase compare to 2022). Interestingly, the proportion of cases in Dhaka city decreased from 51% in 2019 to 34% in 2023. Notably, the southeast and central regions of Bangladesh showed the highest dengue rates, persisting throughout the study period. Cases were concentrated in urban regions, with Dhaka exhibiting the highest caseload in most years, followed by Manikganj in 2023. A distinct temporal shift in dengue transmission was observed in 2023, when the peak incidence occurred three months earlier in July with complete geographic coverage (all the 64 districts) compared to the peak in October 2022 (covering 95%, 61 districts). Positive global autocorrelation analysis revealed spatial dependence, with more stable trends in 2023 compared to previous years. Several districts like, Bagerhat, Barisal, and Faridpur remained persistent hotspots or emerged as new hotspots in 2023. Conversely, districts like Dinajpur, Gaibandha, Nilphamari, Rangpur and Sylhet consistently exhibited low caseloads, categorized as dengue coldspots throughout most of the years. Jhalokati in 2019 and Gopalganj in 2022, both initially classified as low-incidence district surrounded by high-incidence districts, emerged as hotspots in 2023.

CONCLUSION

This study sheds light on the spatiotemporal dynamics of dengue transmission in Bangladesh, particularly by identifying hotspots and clustering patterns. These insights offer valuable information for designing and implementing targeted public health interventions and control strategies. Furthermore, the observed trends highlight the need for adaptable strategies to address the region's evolving nature of dengue transmission effectively.

Geo-spatial high-risk clusters of Tuberculosis in the global general population: a systematic review

INTRODUCTION

The objective of this systematic review is to identify tuberculosis (TB) high-risk among the general population globally. The review was conducted using the following steps: elaboration of the research question, search for relevant publications, selection of studies found, data extraction, analysis, and evidence synthesis.

METHODS

The studies included were those published in English, from original research, presented findings relevant to tuberculosis high-risk across the globe, published between 2017 and 2023, and were based on geospatial analysis of TB. Two reviewers independently selected the articles and were blinded to each other`s comments. The resultant disagreement was resolved by a third blinded reviewer. For bibliographic search, controlled and free vocabularies that address the question to be investigated were used. The searches were carried out on PubMed, LILACS, EMBASE, Scopus, and Web of Science. and Google Scholar.

RESULTS

A total of 79 published articles with a 40-year study period between 1982 and 2022 were evaluated. Based on the 79 studies, more than 40% of all countries that have carried out geospatial analysis of TB were from Asia, followed by South America with 23%, Africa had about 15%, and others with 2% and 1%. Various maps were used in the various studies and the most used is the thematic map (32%), rate map (26%), map of temporal tendency (20%), and others like the kernel density map (6%). The characteristics of the high-risk and the factors that affect the hotspot's location are evident through studies related to poor socioeconomic conditions constituting (39%), followed by high population density (17%), climate-related clustering (15%), high-risk spread to neighbouring cities (13%), unstable and non-random cluster (11%).

CONCLUSION

There exist specific high-risk for TB which are areas that are related to low socioeconomic conditions and spectacular weather conditions, these areas when well-known will be easy targets for intervention by policymakers. We recommend that more studies making use of spatial, temporal, and spatiotemporal analysis be carried out to point out territories and populations that are vulnerable to TB.

Bayesian spatial modelling of tuberculosis-HIV co-infection in Ethiopia

An in-depth analysis of the epidemiological patterns of TB/HIV co-infection is essential since it helps to target high-risk areas with effective control measures. The main objective of this study was to assess the spatial clustering of TB/HIV co-infection prevalence in Ethiopia for the year 2018 using district-level aggregated TB and HIV data obtained from the Ethiopian Federal Ministry of Health. The global Moran's index, Getis-Ord [Formula: see text] local statistic, and Bayesian spatial modeling techniques were applied to analyse the data. The result of the study shows that TB among people living with HIV (PLHIV) and HIV among TB patients prevalence were geographically heterogeneous. The highest prevalence of TB among PLHIV in 2018 was reported in the Gambella region (1.44%). The overall prevalence of TB among PLHIV in Ethiopia in the same year was 0.38% while the prevalence of HIV among TB patients was 6.88%. Both district-level prevalences of HIV among TB patients and TB among PLHIV were positively spatially autocorrelated, but the latter was not statistically significant. The local indicators of spatial analysis using the Getis-Ord statistic also identified hot-spots districts for both types of TB/HIV co-infection data. The results of Bayesian spatial logistic regression with spatially structured and unstructured random effects using the Besag, York, and Mollié prior showed that not all the heterogeneities in the prevalence of HIV among TB patients and TB among PLHIV were explained by the spatially structured random effects. This study expanded knowledge about the spatial clustering of TB among PLHIV and HIV among TB patients in Ethiopia at the district level in 2018. The findings provide information to health policymakers in the country to plan geographically targeted and integrated interventions to jointly control TB and HIV.

Spatial Co-Clustering of Tuberculosis and HIV in Ethiopia

Background: Tuberculosis (TB) and HIV are epidemiologically associated, and their co-dynamics suggest that the two diseases are directly related at the population level and within the host. However, there is no or little information on the joint spatial patterns of the two diseases in Ethiopia. The main objective of the current study was to assess the spatial co-clustering of TB and HIV cases simultaneously in Ethiopia at the district level. Methods: District-level aggregated data collected from the national Health Management Information System (HMIS) for the years 2015 to 2018 on the number of TB cases enrolled in directly observed therapy, short course (DOTS) who were tested for HIV and the number of HIV patients enrolled in HIV care who were screened for TB during their last visit to health care facilities were used in this study. The univariate and bivariate global and local Moran’s I indices were applied to assess the spatial clustering of TB and HIV separately and jointly. Results: The results of this study show that the two diseases were significantly (p-value <0.001) spatially autocorrelated at the district level with minimum and maximum global Moran’s I values of 0.407 and 0.432 for TB, 0.102 and 0.247 for HIV, and 0.152 and 0.251 for joint TB/HIV. The district-level TB/HIV spatial co-clustering patterns in Ethiopia in most cases overlapped with the hot spots of TB and HIV. The TB/HIV hot-spot clusters may appear due to the observed high TB and HIV prevalence rates in the hot-spot districts. Our results also show that there were low-low TB/HIV co-clusters or cold spots in most of the Afar and Somali regions, which consistently appeared for the period 2015−2018. This may be due to very low notifications of both diseases in the regions. Conclusions: This study expanded knowledge about TB and HIV co-clustering in Ethiopia at the district level. The findings provide information to health policymakers in the country to plan geographically targeted and integrated interventions to jointly control TB and HIV.

Sputum smear conversion and associated factors among smear-positive pulmonary tuberculosis patients in East Gojjam Zone, Northwest Ethiopia: a longitudinal study

BACKGROUND

Sputum smear conversion is a key indicator of treatment response and reduced infectivity among bacteriologically confirmed pulmonary tuberculosis (PTB) patients. This study aimed at estimating sputum smear conversion and identifying factors hindering sputum smear conversion among bacteriologically confirmed PTB cases in East Gojjam Zone, Northwest Ethiopia.

METHODS

A total of 282 bacteriologically confirmed PTB patients were followed for 22 weeks through weekly sputum smear examination. Due to the absence of sputum culture and rapid diagnostic services, sputum smear conversion evaluation was conducted microscopically using acid-fast-bacilli staining technique of sediments from a 5% sodium hypochlorite concentration technique. Data on socio-demographic, clinical profile and personal behavior variables were collected using a pretested interviewer-administered questionnaire. Various descriptive statistics including mean, median with interquartile range (IQR), and proportions were computed to describe study objectives. Factors of sputum smear conversion were identified by multivariable logistic regression analysis and statistical significance was determined at a p value < 0.05.

RESULTS

Over half, 166 (59%) of bacteriologically confirmed PTB patients were males and 147 (52%) were rural dwellers. The mean age of respondents was 35 ± 5 SD years. About 88 (31.2%) of bacteriologically confirmed PTB patients had comorbidities, 102 (36.2%) faced stigma, and 54 (19%) history of cigarette smoking. The median sputum smear conversions during the intensive phase and 5th  months of treatment follow up were 35 dyas (IQR: 21-56 days) and 53 days (IQR: 28-82 days), respectuvely. The majority, 85% (95% CI 76-93%) and 95% (95% CI 85-99%) of bacteriologically confirmed PTB patients underwent sputum smear conversion at the end of 2nd and 5th months of treatment, respectively. Poor knowledge on TB, being HIV positive, higher smear grading, having diabetes mellitus, undernutrition, cigarette smoking, facing societal stigma, and TB service delays were positively associated with the length of sputum smear conversion (p value < 0.05).

CONCLUSION

Based on this study, the median sputum smear conversion time was higher compared to TB program expectations and findings from former studies. The study also identified important factors associated with sputum smear conversion time. Improving health literacy of the community by revising the existing community awareness strategies is essential to enhance treatment adherence and lower infectiousness after 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.

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.

TB and HIV Epidemiology and Collaborative Service: Evidence from Ethiopia, 2011-2015

Background

Integrating and scaling up tuberculosis (TB) and HIV services are essential strategies to achieve the combined goals ending both TB and HIV, especially in TB and HIV high burden countries. This study aimed to examine the prevalence of TB and HIV co-infection and the implementation of collaborative services in Ethiopia.

Methods

We used a national sentinel surveillance TB/HIV co-infection collected between 2010 and 2015. The Ethiopian Public Health Institute collected and collated the data quarterly from 79 health facilities in nine regional states and two city administrations.

Results

A total of 55,336 people living with HIV/AIDS were screened for active TB between 2011 and 2015. Of these, 7.3% were found co-infected with TB, and 13% TB-negative PLWHA were on isoniazid preventive therapy. Nine out of ten (89.2%) active TB patients were screened for HIV counselling and 17.8% were found to be HIV positive; 78.2% and 53.0% of HIV/TB co-infected patients were receiving cotrimoxazole preventive therapy and antiretroviral treatment, respectively.

Conclusion

This study showed that the prevalence of TB and HIV co-infection failed to decrease over the study period, and that, while there was an increasing trend for integration of collaborative services, this was not uniform over time. Aligning and integrating TB and HIV responses are still needed to achieve the target of ending TB and HIV by 2030.

Circulating mRNA and microRNA profiling analysis in patients with ischemic stroke

To provide insight into molecular diagnosis and individualized treatment of ischemic stroke (IS), several available datasets in IS were analyzed to identify the differentially expressed genes and microRNAs (miRNAs). Series matrix files from GSE22255 and GSE16561 (mRNA profiles), a well as GSE110993 (miRNA profile) were downloaded from the Gene Expression Omnibus database. System-level clustering was performed with GeneCluster 3.0 software, and gene annotation and pathway enrichment were performed with gene ontology analysis and Database for Annotation, Visualization and Integrated Discovery software. For a protein-protein interaction (PPI) network, Biological General Repository for Interaction Datasets and IntAct interaction information were integrated to determine the interaction of differentially expressed genes. The selected miRNA candidates were imported into the TargetScan, miRDB and miRecords databases for the prediction of target genes. The present study identified 128 upregulated and 231 downregulated genes in female stroke patients, and 604 upregulated and 337 downregulated genes in male stroke patients compared with sex- and age-matched controls. The construction of a PPI network demonstrated that male stroke patients exhibited YWHAE, CUL3 and JUN as network center nodes, and in female patients CYLD, FOS and PIK3R1 interactions were the strongest. Notably, these interactions are mainly involved in immune inflammatory response, apoptosis and other biological pathways, such as blood coagulation. Female and male upregulated genes were cross-validated with another set of Illumina HumanRef-8 v3.0 expression beadchip (GSE16561). Functional item association networks, gene function networks and transcriptional regulatory networks were successfully constructed, and the relationships between miRNAs and target genes were successfully predicted. The present study identified a number of transcription factors, including DEFA1, PDK4, SDPR, TCN1 and MMP9, and miRNAs, including miRNA (miR)-21, miR-143/145, miR-125-5p and miR-122, which may serve important roles in the development of cerebral stroke and may be important molecular indicators for the treatment of IS.