Spatial patterns of tuberculosis and HIV co-infection in Ethiopia

Proportion of active tuberculosis among HIV-infected children after antiretroviral therapy in Ethiopia: A systematic review and meta-analysis

Despite effectiveness of antiretroviral therapy in reducing mortality of opportunistic infections among HIV infected children, however tuberculosis (TB) remains a significant cause for morbidity and attributed for one in every three deaths. HIV-infected children face disproportionate death risk during co-infection of TB due to their young age and miniatures immunity makes them more vulnerable. In Ethiopia, there is lack of aggregated data TB and HIV mortality in HIV infected children. We conducted an extensive systematic review of literature using Preferred Reporting of Systematic Review and Meta-Analysis (PRISMA) guideline. Five electronic databases were used mainly Scopus, PubMed, Medline, Web of Science, and Google scholar for articles searching. The pooled proportion of TB was estimated using a weighted inverse variance random-effects meta-regression using STATA version-17. Heterogeneity of the articles was evaluated using Cochran's Q test and I2 statistic. Subgroup analysis, sensitivity test, and Egger's regression were conducted for publication bias. This met-analysis is registered in Prospero-CRD42024502038. In the final met-analysis report, 13 out of 1221 articles were included and presented. During screening of 6668 HIV-infected children for active TB occurrence, 834 cases were reported after ART was initiated. The pooled proportion of active TB among HIV infected children was found 12.07% (95% CI: 10.71-13.41). In subgroup analysis, the Oromia region had 15.6% (95%CI: 10.2-20.6) TB burden, followed by southern Ethiopia 12.8% (95%CI: 10.03-15.67). During meta-regression, missed isoniazid Preventive therapy (IPT) (OR: 2.28), missed contrimoxazole preventive therapy (OR: 4.26), WHO stage III&IV (OR: 2.27), and level of Hgb ≤ 10gm/dl (OR = 3.11.7) were predictors for active TB. The systematic review found a higher proportion of active TB in HIV-infected children in Ethiopia compared to estimated rates in end TB strategy. To prevent premature death during co-infection, implement effective TB screening and cases tracing strategies in each follow up is needed.

Clusters of heterogeneity of tuberculosis-HIV coinfection in Brazil: a geospatial study

OBJECTIVE

To analyze the geospatialization of tuberculosis-HIV coinfection in Brazil, from 2010 to 2021, and the correlation with socioeconomic, housing, and health indicators.

METHODS

An ecological study of Brazilian municipalities and states, with data from HIV and tuberculosis information systems, previously reported by the Ministry of Health. The crude and smoothed coefficients were calculated by the local empirical Bayesian method of incidence of coinfection per 100,000 inhabitants in the population aged between 18 and 59 years. Univariate (identification of clusters) and bivariate (correlation with 20 indicators) Moran's indices were used.

RESULTS

A total of 122,223 cases of coinfection were registered in Brazil from 2010 to 2021, with a mean coefficient of 8.30/100,000. The South (11.44/100,000) and North (9.93/100,000) regions concentrated the highest burden of infections. The coefficients dropped in Brazil, in all regions, in the years of covid-19 (2020 and 2021). The highest coefficients were observed in the municipalities of the states of Rio Grande do Sul, Mato Grosso do Sul, and Amazonas, with high-high clusters in the capitals, border regions, coast of the country. The municipalities belonging to the states of Minas Gerais, Bahia, Paraná, and Piauí showed low-low clusters. There was a direct correlation with human development indices and aids rates, as well as an indirect correlation with the proportion of poor or of those vulnerable to poverty and the Gini index.

CONCLUSIONS

The spatial analysis of tuberculosis-HIV coinfection showed heterogeneity in the Brazilian territory and constant behavior throughout the period, revealing clusters with high-burden municipalities, especially in large urban centers and in states with a high occurrence of HIV and/or tuberculosis. These findings, in addition to alerting to the effects of the covid-19 pandemic, can incorporate strategic planning for the control of coinfection, aiming to eliminate these infections as public health problems by 2030.

HIV and AIDS in the state of Paraná, Brazil, 2007-2022: trends and spatiotemporal distribution

OBJECTIVE

The aim of this study was to analyze the spatiotemporal evolution of the incidence rates of human immunodeficiency virus (HIV) and acquired immune deficiency syndrome (AIDS) in the state of Paraná, Brazil.

METHODS

An ecological study with an analytical component of time series analysis was conducted in the state of Paraná from 2007 to 2022. The data source was the Notifiable Diseases Information System. To study the trend, the Prais-Winsten generalized linear regression model was used by decomposing the time series, and for spatial analysis, the Moran's index was applied.

RESULTS

The total sample consisted of 50,676 HIV/AIDS records. The incidence rate showed an increasing trend, with an average growth of 2.14% [95% confidence interval - 95%CI 1.16-3.13] per month. From 2007 to 2014 and from 2015 to 2022, the average number of cases in the state was 105.64 and 159.20 per 100,000 inhabitants, respectively, with significant variation among municipalities. Spatial clusters of high risk persisted in the metropolitan region, the capital, and coastal areas, and a new cluster was observed in the northern region of the state.

CONCLUSION

The incidence rates of HIV/AIDS showed an upward trend over time. The number of cases varied considerably in some municipalities, especially in the coastal region. Spatial analysis revealed geospatial patterns of high risk in the main metropolitan areas of Paraná: Curitiba (including the coastal area), Londrina, and Maringá, which share characteristics such as a high degree of urbanization and ongoing economic development.

Active tuberculosis incidence among treatment failure experienced patients in North Wollow Zone: A multicenter historical cohort

Background

In Ethiopia, tuberculosis (TB) is a significant cause of death among individuals living with HIV, especially in resource-limited areas and those who have experienced treatment failure. However, there is the paucity of data regarding TB among treatment failures experienced people living with HIV. This study aimed to estimate the rate and identify predictors of tuberculosis among patients who received second-line treatment in North Wollo, Northeast Ethiopia.

Methods

A retrospective follow-up study was conducted on 474 HIV-infected patients who experienced treatment failure. The study period ranged from January 2015 to September 30, 2021. The incidence of TB was assessed using a Cox proportional hazard regression model, after ensuring that all assumptions were met. Factors associated with active TB were determined by analyzing adjusted hazard ratios and 95% confidence intervals.

Results

In a study of 474 HIV-positive patients on second-line antiretroviral treatment, we found an incidence rate of 3.6% with 17 new cases of TB observed over 4412.4 persons per year (PPY). The overall incidence density rate was estimated to be 0.39 cases per 100 PPY (95% CI: 0.239-0.618). Regarding the occurrence of active TB in second-line patients, WHO clinical treatment stage (T3 and T4), missed isoniazid preventive therapy had a significantly higher risk (AHR: 13.225, 95% CI: 2.894-60.434, p = 0.001), while being married was associated with a lower risk (AHR: 0.203, 95% CI: 0.045-0.907, p = 0.001).

Conclusion

A high incidence of active TB was observed shortly after initiating second-line antiretroviral treatment. Factors such as being in the WHO clinical treatment stage (T3 and T4) and marital status were determinants for active TB. To improve overall survival rates, it is vital to enhance early TB screening and implement effective isoniazid preventive therapy.

Treatment Outcomes of Tuberculosis and Associated Factors Among Tuberculosis and Human Immunodeficiency Virus Co-infected Patients in Public Health Facilities in Jigjiga, Somali Region, Ethiopia

BACKGROUND

Worldwide, tuberculosis (TB) is a serious public health issue, especially in low-income countries, including Ethiopia. For those who are HIV-positive, TB poses a major risk to their health. The development of chemotherapy and the effectiveness of treatment have resulted in notable increases in patient survival. The evaluation of TB treatment outcomes is an essential metric for determining the success of TB and HIV co-morbidity control strategies.

PURPOSE

This study aims to identify TB treatment outcomes and associated factors among TB/HIV co-infected patients in public health facilities in Jigjiga, Somali Region, Ethiopia, in 2021.

PATIENTS AND METHODS

A hospital-based cross-sectional study design was done on three facilities (Karamara, Hasan Yabare Referral Hospital, and Jigjiga Health Center) with a total of 194 study participants. Data were extracted using a checklist, entered into EpiData version 3 (The EpiData Association, Odense, Denmark), and analyzed using SPSS Statistics version 20 (IBM Corp. Released 2011. IBM SPSS Statistics for Windows, Version 20.0. Armonk, NY: IBM Corp.) for descriptive and inferential analysis of the study objectives. Variables in the bivariate logistic regression analysis with p-values less than 0.25 were entered into a multivariate logistic regression to identify the independent factors of TB treatment outcome. Associations were computed using an adjusted odds ratio with a 95% CI. P-values less than 0.05 were finally considered statistically significant.

RESULTS

The following TB treatment outcomes were observed among all TB/HIV co-infected patients enrolled in this study: 126 (67.4%) completed treatment, three (1.8%) died, 42 (22.5%) were cured, and 16 (8.6%) were transferred out; 168 (89.8%) had a successful treatment outcome. Category of the patient (AOR = 0.194, 95% CI: 0.041, 0.923), sex of the patient (AOR = 1.490, 95% CI: 1.449, 4.951), and cotrimoxazole preventive therapy (CPT) initiation (AOR = 0.073, 95% CI: 0.021, 0.254) were found to be significant predictors for successful TB treatment outcome at a p-value less than 0.05 with a 95% CI.

CONCLUSION

Overall, 89.8% of TB treatments were successful among TB/HIV co-infected patients. This study has found sex, socioeconomic status, and CPT initiation were significant factors for a successful TB treatment outcome. Based on these findings, governmental and non-governmental organizations should facilitate the implementation and enforce the availability of all TB/HIV co-infected patients.

Spatial distribution and determinants of tuberculosis incidence in Mozambique: A nationwide Bayesian disease mapping study

INTRODUCTION

Mozambique is a high-burden country for tuberculosis (TB). International studies show that TB is a disease that tends to cluster in specific regions, and different risk factors (HIV prevalence, migration, overcrowding, poverty, house condition, temperature, altitude, undernutrition, urbanization, and inadequate access to TB diagnosis and treatment) are reported in the literature to be associated with TB incidence. Although Mozambique has a higher burden of TB, the spatial distribution, and determinants of TB incidence at the sub-national level have not been studied yet for the whole country. Therefore, we aimed to analyze the spatial distribution and determinants of tuberculosis incidence across all 154 districts of Mozambique and identify the hotspot areas.

METHOD

We conducted an ecological study with the district as our unit of analysis, where we included all cases of tuberculosis diagnosed in Mozambique between 2016 and 2020. We obtained the data from the Mozambique Ministry of Health and other publicly available open sources. The predictor variables were selected based on the literature review and data availability at the district level in Mozambique. The parameters were estimated through Bayesian hierarchical Poisson regression models using Markov Chain Monte Carlo simulation.

RESULTS

A total of 512 877 people were diagnosed with tuberculosis in Mozambique during our five-year study period. We found high variability in the spatial distribution of tuberculosis incidence across the country. Sixty-two districts out of 154 were identified as hotspot areas. The districts with the highest incidence rate were concentrated in the south and the country's central regions. In contrast, those with lower incidence rates were mainly in the north. In the multivariate analysis, we found that TB incidence was positively associated with the prevalence of HIV (RR: 1.23; 95 % CrI 1.13 to 1.34) and negatively associated with the annual average temperature (RR: 0.83; 95 % CrI 0.74 to 0.94).

CONCLUSION

The incidence of tuberculosis is unevenly distributed across the country. Lower average temperature and high HIV prevalence seem to increase TB incidence. Targeting interventions in higher-risk areas and strengthening collaboration between HIV and TB programs is paramount to ending tuberculosis in Mozambique, as established by the WHO's End TB strategy and the Sustainable Development Goals.

Geospatial Overlap of Undernutrition and Tuberculosis in Ethiopia

Undernutrition is a key driver of the global tuberculosis (TB) epidemic, yet there is limited understanding regarding the spatial overlap of both diseases. This study aimed to determine the geographical co-distribution and socio-climatic factors of undernutrition and TB in Ethiopia. Data on undernutrition were found from the Ethiopian Demographic and Health Survey (EDHS). Data on TB were obtained from the Ethiopia national TB prevalence survey. We applied a geostatistical model using a Bayesian framework to predict the prevalence of undernutrition and TB. Spatial overlap of undernutrition and TB prevalence was detected in the Afar and Somali regions. Population density was associated with the spatial distribution of TB [β: 0.008; 95% CrI: 0.001, 0.014], wasting [β: -0.017; 95% CrI: -0.032, -0.004], underweight [β: -0.02; 95% CrI: -0.031, -0.011], stunting [β: -0.012; 95% CrI: -0.017, -0.006], and adult undernutrition [β: -0.007; 95% CrI: -0.01, -0.005]. Distance to a health facility was associated with the spatial distribution of stunting [β: 0.269; 95% CrI: 0.08, 0.46] and adult undernutrition [β: 0.176; 95% CrI: 0.044, 0.308]. Healthcare access and demographic factors were associated with the spatial distribution of TB and undernutrition. Therefore, geographically targeted service integration may be more effective than nationwide service integration.

Geoprogrammatic disparities in the performance of tuberculosis indicators in the homeless population in Brazil: an ecological approach

OBJECTIVE

To analyze the performance and spatial distribution of tuberculosis control indicators in the homeless population in Brazil.

METHODS

Ecological study, which had the regions and federal units of Brazil as the unit of analysis. The indicators considered, referring to the period from 2015 to 2021, were: proportion of HIV testing, proportion of tuberculosis-HIV co-infection, proportion of directly observed treatment, and proportion of outcomes (cure, treatment abandonment and death). The calculation was performed on each ecological unit, as recommended by the Ministry of Health. For the production of geographic figures, the technique of natural breaks was used.

RESULTS

It was identified that people living on the streets had: low HIV testing, especially in Pará (71.7%); high proportion of tuberculosis-HIV coinfection, especially in Rio Grande do Sul (39.9%); and unsatisfactory implementation of directly observed treatment, mainly in Paraíba (7.7%). With regard to outcomes, there was a high rate of treatment abandonment, with a higher proportion in Roraima (52.9%), and a high number of deaths, with an emphasis on Mato Grosso do Sul (23.1%), which also recorded the worst cure rate (28.7%).

CONCLUSION

There was evidence of poor performance of tuberculosis control indicators in homeless people, with heterogeneous distribution between states and regions of the country, and it is clear that most of them had insufficient results. These data raise the persistence of difficulties and challenges inherent to the implementation of tuberculosis control strategies for this population in the national territory.

Spatial and temporal analysis of tuberculosis incidence in Guinea-Bissau, 2018 to 2020

OBJECTIVE

to analyze the epidemiological profile, spatial and temporal distribution of tuberculosis in Guinea-Bissau from 2018 to 2020.

METHODS

an ecological study, carried out in Guinea-Bissau, considering new cases of tuberculosis. Spatial analysis of areas was used to verify tuberculosis distribution in the country, and time series were used to identify incidence evolution over the years of study.

RESULTS

a total of 6,840 new cases of tuberculosis were reported. Tuberculosis incidence rate in the country ranged from 36.8 to 267.7 cases/100,000 inhabitants, with emphasis on the regions of Bissau and Biombo (over 90 cases/100,000). By using time series, it was possible to observe an increase in case incidence over the years of study.

CONCLUSIONS

the study made it possible to identify the epidemiological profile of tuberculosis in Guinea-Bissau, spatial distribution heterogeneity, in addition to identifying the disease evolution over the years of investigation.

Spatiotemporally Comparative Analysis of HIV, Pulmonary Tuberculosis, HIV-Pulmonary Tuberculosis Coinfection in Jiangsu Province, China

Purpose

Pulmonary tuberculosis (PTB) is a severe chronic communicable disease that causes a heavy disease burden in China. Human Immunodeficiency Virus (HIV) and PTB coinfection dramatically increases the risk of death. This study analyzes the spatiotemporal dynamics of HIV, PTB and HIV-PTB coinfection in Jiangsu Province, China, and explores the impact of socioeconomic determinants.

Patients and Methods

The data on all notified HIV, PTB and HIV-PTB coinfection cases were extracted from Jiangsu Provincial Center for Disease Control and Prevention. We applied the seasonal index to identify high-risk periods of the disease. Time trend, spatial autocorrelation and SaTScan were used to analyze temporal trends, hotspots and spatiotemporal clusters of diseases. The Bayesian space-time model was conducted to examine the socioeconomic determinants.

Results

The case notification rate (CNR) of PTB decreased from 2011 to 2019 in Jiangsu Province, but the CNR of HIV and HIV-PTB coinfection had an upward trend. The seasonal index of PTB was the highest in March, and its hotspots were mainly distributed in the central and northern parts, such as Xuzhou, Suqian, Lianyungang and Taizhou. HIV had the highest seasonal index in July and HIV-PTB coinfection had the highest seasonal index in June, with their hotspots mainly distributed in southern Jiangsu, involving Nanjing, Suzhou, Wuxi and Changzhou. The Bayesian space-time interaction model showed that socioeconomic factor and population density were negatively correlated with the CNR of PTB, and positively associated with the CNR of HIV and HIV-PTB coinfection.

Conclusion

The spatial heterogeneity and spatiotemporal clusters of PTB, HIV and HIV-PTB coinfection are exhibited obviously in Jiangsu. More comprehensive interventions should be applied to target TB in the northern part. While in southern Jiangsu, where the economic level is well-developed and the population density is high, we should strengthen the prevention and control of HIV and HIV-PTB coinfection.

Spatial Clustering of Tuberculosis-HIV Coinfection in Ethiopia at Districts Level

Background

Tuberculosis (TB) is a preventable and treatable disease but it is the leading cause of death among people living with HIV (PLHIV). In addition, the emergence of the HIV pandemic has also had a major impact on TB incidence rates. There are studies in spatial patterns of TB and HIV separately in Ethiopia; there is, however, no information on spatial patterns of TB-HIV coinfection in the country at the districts level at least using yearly data. This paper, therefore, aimed at determining the spatial clustering of TB-HIV coinfection prevalence rates in the country at the districts level on an annual basis over a four-year period, 2015-2018.

Methods

District-level aggregated data on the number of TB-HIV infections were obtained from the Ethiopian Federal Ministry of Health for 2015 to 2018. The univariate and bivariate global Moran's index, Getis-Ord G _i ^∗ local statistic, a chi-square test, and a modified t-test statistic for Spearman's correlation coefficient were used to evaluate the spatial clustering and spatial heterogeneity of TB among PLHIV and HIV among TB patients prevalence rates.

Results

The district-level prevalence rate of HIV among TB patients was positively and significantly spatially autocorrelated with global Moran's I values range between 0.021 and 0.134 (p value <0.001); however, the prevalence of TB among PLHIV was significant only for 2015 and 2017 (p value <0.001). Spearman's correlation also shows there was a strong positive association between the two prevalence rates over the study period. The local indicators of spatial analysis using the Getis-Ord statistic revealed that hot-spots for TB among PLHIV and HIV among TB patients have appeared in districts of various regions and the two city administrations in the country over the study period; however, the geographical distribution of hotspots varies over the study period. Similar trends were also observed for the cold-spots except for 2017 and 2018 where there were no cold-spots for TB among PLHIV.

Conclusions

The study presents detailed knowledge about the spatial clustering of TB-HIV coinfection in Ethiopia at the districts level, and the results could provide information for planning coordinated district-specific interventions to jointly control both diseases in Ethiopia.

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.

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.

Care during ART scale-up: surviving the HIV epidemic in Ethiopia

Over the last decades, there has been a worldwide rise of new technologies for controlling the HIV epidemic by expanding antiretroviral medicines. This article examines how the pharmaceutical-driven model of public health, which emerged as a byproduct of antiretroviral treatment (ART) scale-up in Ethiopia, interplayed with local forms of actions, engagements, and voices through which suffering inflicted by the epidemic was cared for. Through the eyes of an Ethiopian woman with HIV, this article illustrates how the increasing emphasis on ART facilitated the defunding of some community-based care practices. Moreover, it rendered the realities of precarious life with HIV invisible in the landscape of therapeutic citizenship. However, for Ethiopians, ART scale-up unfolded amid multiple forms of HIV care practices and relationships that endured stigma, alienation, and uncertainty before and after ART. The experience of surviving the HIV epidemic in Ethiopia provides a vital premise upon which claims of meaningful care are made, and ways to otherwise develop healthcare actions and engagements are sought.

Investigating Spatial Patterns of Pulmonary Tuberculosis and Main Related Factors in Bandar Lampung, Indonesia Using Geographically Weighted Poisson Regression

Tuberculosis (TB) is a highly infectious disease, representing one of the major causes of death worldwide. Sustainable Development Goal 3.3 implies a serious decrease in the incidence of TB cases. Hence, this study applied a spatial analysis approach to investigate patterns of pulmonary TB cases and its drivers in Bandar Lampung (Indonesia). Our study examined seven variables: the growth rate of pulmonary TB, population, distance to the city center, industrial area, green open space, built area, and slum area using geographically weighted Poisson regression (GWPR). The GWPR model demonstrated excellent results with an R2 and adjusted R2 of 0.96 and 0.94, respectively. In this case, the growth rate of pulmonary TB and population were statistically significant variables. Spatial pattern analysis of sub-districts revealed that those of Panjang and Kedaton were driven by high pulmonary TB growth rate and population, whereas that of Sukabumi was driven by the accumulation of high levels of industrial area, built area, and slums. For these reasons, we suggest that local policymakers implement a variety of infectious disease prevention and control strategies based on the spatial variation of pulmonary TB rate and its influencing factors in each sub-district.

Space-Time Distribution Characteristics of Tuberculosis and Its Socioeconomic Factors in Southern China from 2015 to 2019

Purpose

Guangxi is a high prevalence area of tuberculosis (TB) in China, urgent needing of further TB reduction. Our purpose is to analyze the epidemiological characteristics of TB in Guangxi and analyze the relationship between socioeconomic factors and TB from the dimensions of time and space to provide evidence to effectively prevent and control TB.

Patients and Methods

We performed a retrospective analysis of the epidemiology of TB. Moran’s index (I) was used for spatial autocorrelation analysis, and space-time scanning was used to detect temporal, space, and space-time clusters of TB. A Bayesian space-time model was used to analyze related factors of the TB epidemic at the county level in Guangxi.

Results

From 2015 to 2019, a total of 233,623 TB cases were reported in Guangxi. The majority of TB cases were in males; the reported incidence of TB was the highest in people aged ≥65 years. By occupation, farmers were the most frequently affected. The overall reported incidence of TB decreased by 4.95% during this period. Tuberculosis occurs all year round, but the annual reporting peak is usually from March to July. Spatial autocorrelation analysis showed that the reported incidence of TB in 2015–2019 was spatially clustered (Moran’s I > 0, P < 0.05); Kulldorff’s scan revealed that the space-time cluster (log-likelihood ratio = 2683.76, relative risk = 1.60, P < 0.001) was mainly concentrated in northern Guangxi. Using Bayesian space-time modeling, socioeconomic and healthcare factors are related to the high prevalence of TB.

Conclusion

The prevalence of TB is influenced by a space-time interaction effect and is associated with socioeconomic and healthcare status. It is necessary to improve the economic development and health service in areas with a high TB prevalence.

Spatial codistribution of HIV, tuberculosis and malaria in Ethiopia

Background

HIV, tuberculosis (TB) and malaria are the three most important infectious diseases in Ethiopia, and sub-Saharan Africa. Understanding the spatial codistribution of these diseases is critical for designing geographically targeted and integrated disease control programmes. This study investigated the spatial overlap and drivers of HIV, TB and malaria prevalence in Ethiopia.

Methods

HIV, TB and malaria data were obtained from different nationwide prevalence surveys, and geospatial covariates were obtained from publicly available sources. A Bayesian model-based geostatistical framework was applied to each survey leveraging the strength of high-resolution spatial covariates to predict continuous disease-specific prevalence surfaces and their codistribution.

Results

The national prevalence was 1.54% (95% CI 1.40 to 1.70) for HIV, 0.39% (95% CI 0.34 to 0.45) for TB and 1.1% (95%CI 0.95 to 1.32) for malaria. Substantial subnational variation was predicted with the highest HIV prevalence estimated in Gambela (4.52%), Addis Ababa (3.52%) and Dire Dawa (2.67%) regions. TB prevalence was highest in Dire Dawa (0.96%) and Gambela (0.88%), while malaria was highest in Gambela (6.1%) and Benishangul-Gumuz (3.8%). Spatial overlap of their prevalence was observed in some parts of the country, mainly Gambela region. Spatial distribution of the diseases was significantly associated with healthcare access, demographic, and climatic factors.

Conclusions

The national distribution of HIV, TB and malaria was highly focal in Ethiopia, with substantial variation at subnational and local levels. Spatial distribution of the diseases was significantly associated with healthcare access, demographic and climatic factors. Spatial overlap of HIV, TB and malaria prevalence was observed in some parts of the country. Integrated control programmes for these diseases should be targeted to these areas with high levels of co-endemicity.

Estimating district HIV prevalence in Zambia using small-area estimation methods (SAE)

Background

The HIV/AIDS pandemic has had a very devastating impact at a global level, with the Eastern and Southern African region being the hardest hit. The considerable geographical variation in the pandemic means varying impact of the disease in different settings, requiring differentiated interventions. While information on the prevalence of HIV at regional and national levels is readily available, the burden of the disease at smaller area levels, where health services are organized and delivered, is not well documented. This affects the targeting of HIV resources. There is need, therefore, for studies to estimate HIV prevalence at appropriate levels to improve HIV-related planning and resource allocation.

Methods

We estimated the district-level prevalence of HIV using Small-Area Estimation (SAE) technique by utilizing the 2016 Zambia Population-Based HIV Impact Assessment Survey (ZAMPHIA) data and auxiliary data from the 2010 Zambian Census of Population and Housing and the HIV sentinel surveillance data from selected antenatal care clinics (ANC). SAE models were fitted in R Programming to ascertain the best HIV predicting model. We then used the Fay–Herriot (FH) model to obtain weighted, more precise and reliable HIV prevalence for all the districts.

Results

The results revealed variations in the district HIV prevalence in Zambia, with the prevalence ranging from as low as 4.2% to as high as 23.5%. Approximately 32% of the districts (n = 24) had HIV prevalence above the national average, with one district having almost twice as much prevalence as the national level. Some rural districts have very high HIV prevalence rates.

Conclusions

HIV prevalence in Zambian is highest in districts located near international borders, along the main transit routes and adjacent to other districts with very high prevalence. The variations in the burden of HIV across districts in Zambia point to the need for a differentiated approach in HIV programming within the country. HIV resources need to be prioritized toward districts with high population mobility.

The Effect of Long-Term HAART on the Incidence of Tuberculosis Among People Living with HIV in Addis Ababa, Ethiopia: A Matched Nested Case-Control Study

Background

The introduction of antiretroviral therapy (ART) significantly decreases the incidence of tuberculosis (TB) in people living with human immunodeficiency virus (PLWHIV). However, a considerable proportion is still co-infected with TB after ART initiation. Thus, this study aimed to assess the effect of long-term HAART on the incidence of TB among PLWHIV in Addis Ababa, Ethiopia.

Methods

A matched nested case–control study was conducted among PLWHIV who were enrolled in ART clinics in Addis Ababa, Ethiopia from 2013 up to 2018. Cases were HIV-TB co-infected individuals who were taking antiretroviral treatment, while controls were PLWHIV without TB who were taking antiretroviral treatment. The cases and controls are matched exactly in age and sex. Data were entered in Epi Info version 7.1 and analyzed using SPSS version 20. Bi-variable and multivariable conditional logistic regression were employed along with 95% CI. A P-value <0.05 in the multivariable analysis was considered statistically significant.

Results

Fifty-seven cases were compared with 114 controls. Accordingly, previous TB history (X²; 13.790, P < 0.001), baseline functional status (X²; 9.120, P = 0.010), baseline WHO clinical stage (X²; 10.083, P = 0.001), baseline hemoglobin value (X²; 6.985, P = 0.008), baseline body mass index (X²; 3.873, P = 0.049), isoniazid preventive treatment (X²; 8.047, P = 0.005), baseline CD4 value (X²; 12.741, P < 0.001) and length of stay on ART (X²; 53.359, P < 0.001) were associated with developing TB. Length of stay on ART was found to be the statistically significant determinant of TB infection after ART initiation (aOR = 5.925, 95% CI = 2.649–13.250).

Conclusion

Advanced clinical stages at the baseline, previous TB history, and not taking IPT were associated with TB infection. The long-term ART exposure significantly decreases tuberculosis incidence in PLWHIV. Thus, retaining PLWHIV on ART would be important to decrease the incidence of TB in this group of individuals.

Time to Develop and Predictors for Incidence of Tuberculosis among Children Receiving Antiretroviral Therapy

Infection by the human immune deficiency virus (HIV) is the strongest risk factor for latent or new infection of tuberculosis (TB) through reduction of CD4 T-lymphocytes and cellular immune function. Almost one-third of deaths among people living with HIV are attributed to tuberculosis. Despite this evidence, in Ethiopia, there is a scarcity of information regarding the incidence of tuberculosis for children living with HIV. Thus, this study assessed time to develop and predictors for incidence of tuberculosis in children attending HIV/AIDS care in public hospitals: North West Ethiopia 2021. Methods. A facility-based retrospective cohort study was conducted among 421 seropositive children on antiretroviral therapy in two hospitals between January 1, 2011 and December 31, 2020. EPI-DATA version 3.2 and STATA/14 software were used for data entry and analysis, respectively. Tuberculosis-free survival time was estimated using the Kaplan-Meier survival curve. Bivariate and multivariable Cox regression model was fitted to identify predictors at a P value <0.05 within 95% CI. Results. In the final analysis, a total of 421 seropositive children were included, of whom, 64 (15.2%) developed tuberculosis at the time of follow-up. The mean (±SD) age of the children was 10.62 ± 3.32 years, with a median (IQR) time to develop TB that was 23.5 (IQR = ±19) months. This study found that the incidence of tuberculosis was 5.9 (95% CI: 4.7; 7.6) per 100 person-years (PY) risk of observation. Cases at baseline not taking cotrimoxazol preventive therapy (CPT) (AHR = 2.5; 95% CI, 1.4-4.7, P < 0.021), being severely stunted (AHR = 2.9: 95% CI, 1.2-7.8, P < 0.03), and having low hemoglobin level (AHR = 4.0; 95% CI, 2.1-8.1, P < 0.001) were found to be predictors of tuberculosis. Conclusion. A higher rate of tuberculosis incidence was reported in our study as compared with previous studies in Ethiopia. Cases at baseline not taking cotrimoxazol preventive therapy (CPT), being severely stunted, and having low hemoglobin (≤10 mg/dl) levels were found to be at higher risk to developed TB incidence.

Environmental influence on <em>Triatoma vitticeps</em> occurrence and <em>Trypanosoma cruzi</em> infection in the Atlantic Forest of south-eastern Brazil

Trypanosoma cruzi requires a triatomine insect vector for its life cycle, which can be complex in different enzootic scenarios, one of which is the unique transmission network in the Atlantic Forest of south-eastern Brazil. In Espírito Santo (ES) State, highly infected Triatoma vitticeps are frequently reported invading domiciles. However, triatomines were not found colonizing residences and mammals in the surrounding areas did not present T. cruzi infection. To date, the biotic and abiotic variables that modulate T. vitticeps occurrence and T. cruzi infection in ES State are still unknown. The aim of this study was to identify the environmental variables that modulate their occurrence. Local thematic maps were generated for two response variables: T. vitticeps occurrence and T. cruzi infection. The following explanatory variables were tested: climate (temperature, relative air humidity and rainfall), altitude elevation, mammalian species richness as well as soil and vegetation types. Spatiotemporal distribution patterns and correlation levels between response and explanatory variables were assessed through spatial statistics and map algebra modelling. The central and southern mesoregions presented higher T. vitticeps and T. cruzi distributions and can be considered transmission hotspots. The explanatory variables that can explain these phenomena were relative air humidity, average temperature, soil type, altitude elevation and mammalian species richness. Algebra map modelling demonstrated that central and southern mesoregions presented the environmental conditions needed for T. vitticeps occurrence and T. cruzi infection. The consideration of environmental variables is essential for understanding the T. cruzi transmission cycle. Cartographic and statistical methodologies used in parasitology have been demonstrated to be reliable and enlightening tools that should be incorporated routinely to expand the understanding of vector-borne parasite transmission.

Spatiotemporal Patterns of Tuberculosis in Hunan Province, China

Tuberculosis (TB) is the leading cause of death from a bacterial pathogen worldwide. China has the third highest TB burden in the world, with a high reported burden in Hunan Province (amongst others). This study aimed to investigate the spatial distribution of TB and identify socioeconomic, demographic, and environmental drivers in Hunan Province, China. Numbers of reported cases of TB were obtained from the Tuberculosis Control Institute of Hunan Province, China. A wide range of covariates were collected from different sources, including from the Worldclim database, and the Hunan Bureau of Statistics. These variables were summarized at the county level and linked with TB notification data. Spatial clustering of TB was explored using Moran’s I statistic and the Getis–Ord statistic. Poisson regression models were developed with a conditional autoregressive (CAR) prior structure, and with posterior parameters estimated using a Bayesian approach with Markov chain Monte Carlo (MCMC) simulation. A total of 323,340 TB cases were reported to the Hunan TB Control Institute from 2013 to 2018. The mean age of patients was 51.7 years (SD + 17.6 years). The majority of the patients were male (72.6%, n = 234,682) and had pulmonary TB (97.5%, n = 315,350). Of 319,825 TB patients with registered treatment outcomes, 306,107 (95.7%) patients had a successful treatment outcome. The annual incidence of TB decreased over time from 85.5 per 100,000 population in 2013 to 76.9 per 100,000 population in 2018. TB case numbers have shown seasonal variation, with the highest number of cases reported during the end of spring and the beginning of summer. Spatial clustering of TB incidence was observed at the county level, with hotspot areas detected in the west part of Hunan Province. The spatial clustering of TB incidence was significantly associated with low sunshine exposure (RR: 0.86; 95% CrI: 0.74, 0.96) and a low prevalence of contraceptive use (RR: 0.88; 95% CrI: 0.79, 0.98). Substantial spatial clustering and seasonality of TB incidence were observed in Hunan Province, with spatial patterns associated with environmental and health care factors. This research suggests that interventions could be more efficiently targeted at locations and times of the year with the highest transmission risk.

Spatial patterns of pulmonary tuberculosis (TB) cases in Zimbabwe from 2015 to 2018

INTRODUCTION

Accurate mapping of spatial heterogeneity in tuberculosis (TB) cases is critical for achieving high impact control as well as guide resource allocation in most developing countries. The main aim of this study was to explore the spatial patterns of TB occurrence at district level in Zimbabwe from 2015 to 2018 using GIS and spatial statistics as a preamble to identifying areas with elevated risk for prioritisation of control and intervention measures.

METHODS

In this study Getis-Ord Gi* statistics together with SaTscan were used to characterise TB hotspots and clusters in Zimbabwe at district level from 2015 to 2018. GIS software was used to map and visualise the results of cluster analysis.

RESULTS

Results show that TB occurrence exhibits spatial heterogeneity across the country. The TB hotspots were detected in the central, western and southern part of the country. These areas are characterised by artisanal mining activities as well as high poverty levels.

CONCLUSIONS AND RECOMMENDATIONS

Results of this study are useful to guide TB control programs and design effective strategies which are important in achieving the United Nations Sustainable Development goals (UNSDGs).

Mapping tuberculosis prevalence in Ethiopia: protocol for a geospatial meta-analysis

INTRODUCTION

Tuberculosis (TB), a major public health concern in Ethiopia, is distributed heterogeneously across the country. Mapping TB prevalence at national and subnational levels can provide information for designing and implementing control strategies. Data for spatial analysis can be obtained through systematic review of the literature, and spatial prediction can be done by meta-analysis of published data (geospatial meta-analysis). Geospatial meta-analysis can increase the power of spatial analytic models by making use of all available data. It can also provide a means for spatial prediction where new survey data in a given area are sparse or not available. In this report, we present a protocol for a geospatial meta-analysis to investigate the spatial patterns of TB prevalence in Ethiopia.

METHODS AND ANALYSIS

To conduct this study, a national TB prevalence survey, supplemented with data from a systematic review of published reports, will be used as the source of TB prevalence data. Systematic searching will be conducted in PubMed, Scopus and Web of Science for studies published up to 15 April 2020 to identify all potential publications reporting TB prevalence in Ethiopia. Data for covariates for multivariable analysis will be obtained from different, readily available sources. Extracted TB survey and covariate data will be georeferenced to specific locations or the centroids of small administrative areas. A binomial logistic regression model will be fitted to TB prevalence data using both fixed covariate effects and random geostatistical effects based on the approach of model-based geostatistics. Markov Chain Monte Carlo simulation will be conducted to obtained posterior parameter estimations, including spatially predicted prevalence.

ETHICS AND DISSEMINATION

Ethical approval will not be required for this study as it will be based on deidentified, aggregate published data. The final report of this review will be disseminated through publication in a peer-reviewed scientific journal and will also be presented at relevant conferences.

Spatial distribution of Mycobacterium Tuberculosis in metropolitan Harare, Zimbabwe

INTRODUCTION

The contribution of high tuberculosis (TB) transmission pockets in propagating area-wide transmission has not been adequately described in Zimbabwe. This study aimed to describe the presence of hotspot transmission of TB cases in Harare city from 2011 to 2012 using geospatial techniques.

METHODS

Anonymised TB patient data stored in an electronic database at Harare City Health department was analysed using geospatial methods. Confirmed TB cases were mapped using geographic information system (GIS). Global Moran's I and Anselin Local Moran's I (LISA) were used to assess clustering and the local Getis-Ord Gi* was used to estimate hotspot phenomenon of TB cases in Harare City for the period between 2011 and 2012.

RESULTS

A total of 12,702 TB cases were accessed and mapped on the Harare City map. In both 2011 and 2012, ninety (90%) of cases were new and had a high human immunodeficiency virus (HIV)/TB co-infection rate of 72% across all suburbs. Tuberculosis prevalence was highest in the Southern district in both 2011 and 2012. There were pockets of spatial distribution of TB prevalence across West South West, Southern, Western, South Western and Eastern health districts. TB hot spot occurrence was restricted to the West South West, parts of South Western, Western health districts. West South West district had an increased peri-urban population with inadequate social services including health facilities. These conditions were conducive for increased intensity of TB occurrence, a probable indication of high transmission especially in the presence of high HIV co-infection.

CONCLUSIONS AND RECOMMENDATIONS

Increased TB transmission was limited to a health district with high informal internal migrants with limited health services in Harare City. To minimise spread of TB into greater Harare, there is need to improve access to TB services in the peri-urban areas.