Spatial and non-spatial determinants of successful tuberculosis treatment outcomes: An implication of Geographical Information Systems in health policy-making in a developing country

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.

Exploring the criteria and factors affecting firefighters' resilience: A qualitative study

PURPOSE

Firefighters are exposed to high levels of occupational risk factors, such as safety risks, chemical, ergonomic, and physical hazards that may jeopardize their lives. To overcome these hazards, firefighters must be physically, mentally, and personally fit to work. This study aimed to explore the criteria and factors affecting firefighters' resilience based on stakeholders' experiences.

METHODS

This qualitative study was carried out using conventional content analysis. In total, 21 face-to-face interviews were conducted by firefighters who were experienced in the field. The interviews were carried out from July 2019 to January 2020. The data were collected using 3 unstructured interviews and then resumed by 18 semi-structured interviews. Data analysis was done using Graneheim method.

RESULTS

The participants had more than 5 years of experience in the field of search and rescue. The extracted codes through data analysis were classified into 3 main categories (individual, organizational, and social factors), 9 sub-categories (mental, physical, occupational, managerial, colleagues-related, equipment-related, environmental, community-related, and family-related factors), as well as 19 sub-sub-categories and 570 codes.

CONCLUSION

Firefighters' personality, physical condition, behavior and psychological characteristics can affect their resilience along with organizational and management factors that play significant role in people's safety. Developing a tool for assessing resilience can help decision makers to have a real depict of firefighters' job qualifications.

Spatial modeling of mortality from acute lower respiratory infections in children under 5 years of age in 2000-2017: a global study

BACKGROUND

Over the past few decades, various goals have been defined to reduce the mortality of children caused by acute lower respiratory infections (ALRIs) worldwide. However, few spatial studies to date have reported on ALRI deaths.

PURPOSE

We aimed to assess the spatial modeling of mortality from ALRI in children under 5 years of age during 2000-2017 using a global data.

METHODS

The data on the mortality of children under 5 years old caused by ALRI were initially obtained from the official website of the World Health Organization. The income status of their home countries was also gathered from the Country Income Groups (World Bank Classification) website and divided into 5 categories. After that, in the ArcGIS 10.6 environment, a database was created and the statistical tests and related maps were extracted. The Global Moran's I statistic, Getis-Ord Gi statistic, and geographically weighted regression were used for the analyses. In this study, higher z scores indicated the hot spots, while lower z scores indicated the cold spots.

RESULTS

In 2000-2017, child mortality showed a downward trend from 17.6 per 100,000 children to 8.1 and had a clustered pattern. Hot spots were concentrated in Asia in 2000 but shifted toward African countries by 2017. A cold spot that formed in Europe in 2007 showed an ascending trend by 2017. Based on the results of geographically weighted regression test, the regions identified as the hot spots of mortality from ALRI in children under 5 years old were among the middle-income countries (R2=0.01, adjusted R2=8.77).

CONCLUSION

While the total number of child deaths in 2000-2017 has decreased, the number of hot spots has increased among countries. This study also concluded that, during the study period, Central and Western Africa countries became the main new hot spots of deaths from ALRI.

A Spatial Analysis of Tuberculosis Related Mortality in South Africa

Background: South Africa, with an estimated annual tuberculosis (TB) incidence of 360,000 cases in 2019, remains one of the countries with the largest burden of TB in the world. The identification of highly burdened TB areas could support public health policy planners to optimally target resources and TB control and prevention interventions. Objective: To investigate the spatial epidemiology and distribution of TB mortality in South Africa in 2010 and its association with area-level poverty and HIV burden. Methods: The study analysed a total of 776,176 TB deaths for the period 2005-2015. Local and global and spatial clustering of TB death rates were investigated by Global and Local Moran's Indices methods (Moran's I). The spatial regression analysis was employed to assess the effect of poverty and HIV on TB mortality rates. Results: There was a significant decrease in TB mortality rate, from 179 per 100,000 population in 2005 to 60 per 100,000 population in 2015. The annual TB mortality rate was higher among males (161.5 per 100,000 male population; (95% confidence interval (CI) 132.9, 190.0) than among females (123.2 per 100,000 female population; (95% CI 95.6, 150.8)). The 35-44 age group experienced higher TB mortality rates, regardless of gender and time. Hot spot clusters of TB mortality were found in the South-Eastern parts of the country, whereas cold spot clusters were largely in the north-eastern parts. Tuberculosis death rates were positively associated with poverty, as measured by the South African Multidimension Poverty Index (SAMPI) as well TB death rates in the neighbouring districts. Conclusion: The findings of this study revealed a statistically significant decrease in TB deaths and a disproportionate distribution of TB deaths among certain areas and population groups in South Africa. The existence of the identified inequalities in the burden of TB deaths calls for targeted public health interventions, policies, and resources to be directed towards the most vulnerable populations in South Africa.

Factors Influencing Hospital Emergency Evacuation during Fire: A Systematic Literature Review

BACKGROUND

Although the hospital is known as a safe place for treating patients, due to various reasons, it is prone to several internal hazards, including fire. This study aimed to identify the factors affecting hospital emergency evacuation during fire.

METHODS

This was a systematic review conducted according to the PRISMA guideline. Thematic Content analysis was utilized to analyze and extract results. We found the studies investigating the factors affecting hospital emergency evacuation during fire through a comprehensive search in various data resources (MEDLINE, Web of Science, Google Scholar, Embase, ProQuest, Scopus, IRANMEDEX, SID, ISC, and Magiran) and other sources from the beginning of January 2000 to the end of December 2019. Thematic Content analysis was also employed to analyze.

RESULTS

At first and based on the initial search, 4484 studies were identified, and 48 articles were finally included in the study. Based on the results; five main themes along with 10 sub-themes were identified. The themes included the incident's characteristics, response measures, hospital preparedness, hospital residents, and hospital building, and the sub-themes were emergency evacuation features, fire characteristics, command, operation, patients' and staff's characteristics, planning, logistics, and structure and design hospital.

CONCLUSIONS

Based on the results of the present study, hospital preparedness as one of the most important factors can reduce the hospital evacuation time. Therefore, hospitals can ensure a timely and more effective response in emergency evacuation during fire by improving their preparedness.

Association of sociodemographic and environmental factors with spatial distribution of tuberculosis cases in Gombak, Selangor, Malaysia

Tuberculosis (TB) cases have increased drastically over the last two decades and it remains as one of the deadliest infectious diseases in Malaysia. This cross-sectional study aimed to establish the spatial distribution of TB cases and its association with the sociodemographic and environmental factors in the Gombak district. The sociodemographic data of 3325 TB cases such as age, gender, race, nationality, country of origin, educational level, employment status, health care worker status, income status, residency, and smoking status from 1st January 2013 to 31st December 2017 in Gombak district were collected from the MyTB web and Tuberculosis Information System (TBIS) database at the Gombak District Health Office and Rawang Health Clinic. Environmental data consisting of air pollution such as air quality index (AQI), carbon monoxide (CO), nitrogen dioxide (NO2), sulphur dioxide (SO2), and particulate matter 10 (PM10,) were obtained from the Department of Environment Malaysia from 1st July 2012 to 31st December 2017; whereas weather data such as rainfall were obtained from the Department of Irrigation and Drainage Malaysia and relative humidity, temperature, wind speed, and atmospheric pressure were obtained from the Malaysia Meteorological Department in the same period. Global Moran's I, kernel density estimation, Getis-Ord Gi* statistics, and heat maps were applied to identify the spatial pattern of TB cases. Ordinary least squares (OLS) and geographically weighted regression (GWR) models were used to determine the spatial association of sociodemographic and environmental factors with the TB cases. Spatial autocorrelation analysis indicated that the cases was clustered (p<0.05) over the five-year period and year 2016 and 2017 while random pattern (p>0.05) was observed from year 2013 to 2015. Kernel density estimation identified the high-density regions while Getis-Ord Gi* statistics observed hotspot locations, whereby consistently located in the southwestern part of the study area. This could be attributed to the overcrowding of inmates in the Sungai Buloh prison located there. Sociodemographic factors such as gender, nationality, employment status, health care worker status, income status, residency, and smoking status as well as; environmental factors such as AQI (lag 1), CO (lag 2), NO2 (lag 2), SO2 (lag 1), PM10 (lag 5), rainfall (lag 2), relative humidity (lag 4), temperature (lag 2), wind speed (lag 4), and atmospheric pressure (lag 6) were associated with TB cases (p<0.05). The GWR model based on the environmental factors i.e. GWR2 was the best model to determine the spatial distribution of TB cases based on the highest R2 value i.e. 0.98. The maps of estimated local coefficients in GWR models confirmed that the effects of sociodemographic and environmental factors on TB cases spatially varied. This study highlighted the importance of spatial analysis to identify areas with a high TB burden based on its associated factors, which further helps in improving targeted surveillance.

Risk factors associated with road traffic injuries at the prone-areas in Kampala city: a retrospective cross-sectional study

Background:

Road traffic injuries (RTIs) pose a disproportionate public health burden in the low and middle-income countries (LMICs) like Uganda, with 85% of all the fatalities and 90% of all disability-adjusted life years lost reported worldwide. Of all RTIs which are recorded in Uganda, 50% of cases happen in Kampala —the capital city of Uganda and the nearby cities. Identifying the RTI prone-areas and their associated risk factors can help to inform road safety and prevention measures aimed at reducing RTIs, particularly in emerging cities such as Kampala.

Methods:

This study was based on a retrospective cross-sectional design to analyze a five year (2011 – 2015) traffic crash data of the Uganda Police Force.

Results:

Accordingly, 60 RTI prone-areas were identified to exist across the Kampala. They were ranked as low and high risk areas; 41 and 19, respectively and with the majority of the latter based in the main city center. The bivariate analysis showed a significant association between identified prone-areas and population flow (OR: 4.89, P–value: 0.01) and traffic flow time (OR: 9.06, P–value: 0.01). On the other hand, the multivariate regression analysis only showed traffic flow time as the significant predictor (OR: 6.27, P–value: 0.02) at identified RTI prone-areas.

Conclusions:

The measures devised to mitigate RTI in an emerging city like Kampala should study thoroughly the patterns of traffic and population flow to help to optimize the use of available resources for effective road safety planning, injury prevention and sustainable transport systems.

Road safety data collection systems in Iran: A comparison based on relevant organizations

PURPOSE

Various organizations and institutions are involved in road traffic injury (RTI) and crash registration such as police, forensic medicine organization, hospitals and emergency medical services. But there is a substantial uncertainty in interpreting the data, duplicated data collection and missing data in relation to RTI in most systems. This study aims to identify data sources for RTI surveillance in Iran and to explore traffic safety data source domains, data elements and detailed information by each data source.

METHODS

This is a qualitative study which was conducted in 2017 in Iran. Data were collected employing semi-structured interviews with informants in road safety organizations in relation to traffic safety including Police, Ministry of Health and Medical Education as well as Forensic Medicine Organization and other authorities-in-charge. For completing the preliminary extraction information, the minimum data set was used and compared in each system.

RESULTS

Eight different organizations relevant to road traffic safety were identified. The main domain of data provided by each one consists of Emergency Medical System form, Police KAM114 form, Ministry of Transport and Road Administration, Red Crescent Organization/Disaster Management Information System, Ministry of Health and Medical Education, Forensic Medicine Organization, Insurance Company and Ministry of Justice. Each system has its own database, based upon its scope and mainly at crash and post-crash status and little on pre-crash circumstance.

CONCLUSION

All current registry systems are not surveillance systems for RTI prevention. Huge data have been collected in various registry systems in Iran, but most of the collected variables are duplicated in each system. On the other hand, some variables like alcohol and substance abuse, child seat belt, helmet use in relation to RTI prevention are missed in all systems. Accordingly, it is a critical need to integrate and establish a comprehensive surveillance system, with focus on the goal of each system and collection of minimum data in each organization, which currently is underway.

Identification and Prioritization of Key Components Influencing Prehospital Emergency Related to Preventable Road Traffic Injuries Deaths in Iran; A Delphi Study

Objective

To identify and prioritize the key Components of prehospital emergency system to prevent mortality in road traffic injuries.

Methods

A total of 25 emergency medicine practitioners, emergency ward nurses, and managers of prehospital emergency centers participated in this adjusted Delphi study in three rounds. After extracting the primary components through reviewing systematic studies and interviewing experts, the Delphi rounds were performed with the presence of experts. The data were analyzed with both qualitative content analysis and quantitative analysis using SPSS20 software. For the analysis and selection of the final priorities, the coefficient of agreement of over 70% was used.

Results

After doing three Delphi rounds, in the final Delphi round, 10 superior components were selected respectively as follows: correct history taking of the victim, examining possible cervical injury, the time spent from the first call to arrival of technicians to the scene, the time spent from arriving at the scene to the time of hospital transport, passing of re-education courses by EMS technicians, coordination among the rescue organizations, police, the Red Crescent, fire station, and healthcare organizations, integrated commandership at scene, police attendance in the scene before EMS arrival at the scene, proper ambulance equipment with respect to the required equipment (A, B, C) on the basis of victim's condition, and coordination with the target hospital for patient transport.

Conclusion

This study determined the most applicable managerial methods of prehospital emergency components pertaining to preventable fatal road traffic injuries through empowerment of EMS systems in the fields of victim assessment, time management indices, personnel training, coordination between the involved organs, and the presence of the main commander in the scene.

Road traffic injuries measures in the Eastern Mediterranean Region: findings from the Global Status Report on Road Safety - 2015

BACKGROUND

The Eastern Mediterranean Region has the second highest road traffic fatality rate in the world. This article presents the epidemiology of road traffic injuries and the preventive measures in Eastern Mediterranean Region taken by the different World Health Organization member states compared to the rest of the world.

METHODS

This is a secondary data analysis addressing the Global Status Report on Road Safety published by the World Health Organization in 2015. Data are from 180 countries covering 6.97 billion people of the world's population, of which 21 Eastern Mediterranean Region of World Health Organization member states with about 595 million population were included and were analyzed. From 22 countries in the region, 21 are presented and Syria has not reported any data on road traffic injuries.

RESULTS

Eastern Mediterranean Region member states contribute to 9.69% of all global fatal road traffic injuries (19.9 per 100 000 population compared to the same rate in the European region with 9.3), while these countries account for 7.4% of the world's population and have about 5.6% of the world's vehicles on their roads. More than 90% of the Eastern Mediterranean Region countries have passed mandatory seat-belt laws for both front-seat and rear-seat passengers and making helmet use obligatory; and only 27% have child restraint laws; half percent have an emergency room injury surveillance system. All countries have a national drink-driving law; and certain speed limits but there is no distinction between rural and urban areas, and the latter lack adequate speed restrictions.

CONCLUSIONS

Although the Eastern Mediterranean Region member states have some important preventive measures recommended by World Health Organization, considerable efforts are still needed to optimize the enforcement of existing road safety laws. The maximum urban speed limit should be reduced in many countries. Sufficient attention should be paid to the needs of pedestrians, cyclists and motorcyclists, who together make up about 50% of Eastern Mediterranean Region road traffic deaths.

Challenges of establishing a road traffic injury surveillance system: a qualitative study in a middle-income country

BACKGROUND

Establishing effective road traffic injury surveillance is an important priority for low- and middle-income countries since a large proportion of fatal road traffic injuries occur in these countries. A surveillance system can coordinate the activities and compile the data gathered by all road safety organizations. This study aims to explore the challenges of establishing road traffic injury surveillance based on the stakeholders' experiences.

METHODS

This is a qualitative content analysis study that was performed in 2018 in Iran. The study was conducted through interviews with 13 participants and employed purposeful sampling. Data generation was continued until concept saturation.

RESULTS

Five main categories and 17 sub-categories were identified including: policy-making (legal authority, stakeholders, content policy and plan); process (collection and recording, analysis and interpretation, dissemination and feedback); resources and infrastructure (technology, staff, structure, finance); coherence and coordination (communication, dispersion, cooperation, consensus); and context (socio-cultural, political).

CONCLUSIONS

By creating a clear structure for a road traffic injury surveillance system, identifying data collection systems and stakeholders in the field of road safety and injury prevention, determining a clear goal for improving road safety, and formulating policies for the dissemination of road traffic crash data among stakeholders, it will be possible to overcome the obstacles to establishing a surveillance system for road traffic injury.

Mapping tuberculosis treatment outcomes in Ethiopia

BACKGROUND

Tuberculosis (TB) is the leading cause of death from an infectious disease in Ethiopia, killing more than 30 thousand people every year. This study aimed to determine whether the rates of poor TB treatment outcome varied geographically across Ethiopia at district and zone levels and whether such variability was associated with socioeconomic, behavioural, health care access, or climatic conditions.

METHODS

A geospatial analysis was conducted using national TB data reported to the health management information system (HMIS), for the period 2015-2017. The prevalence of poor TB treatment outcomes was calculated by dividing the sum of treatment failure, death and loss to follow-up by the total number of TB patients. Binomial logistic regression models were computed and a spatial analysis was performed using a Bayesian framework. Estimates of parameters were generated using Markov chain Monte Carlo (MCMC) simulation. Geographic clustering was assessed using the Getis-Ord Gi* statistic, and global and local Moran's I statistics.

RESULTS

A total of 223,244 TB patients were reported from 722 districts in Ethiopia during the study period. Of these, 63,556 (28.5%) were cured, 139,633 (62.4%) completed treatment, 6716 (3.0%) died, 1459 (0.7%) had treatment failure, and 12,200 (5.5%) were lost to follow-up. The overall prevalence of a poor TB treatment outcome was 9.0% (range, 1-58%). Hot-spots and clustering of poor TB treatment outcomes were detected in districts near the international borders in Afar, Gambelia, and Somali regions and cold spots were detected in Oromia and Amhara regions. Spatial clustering of poor TB treatment outcomes was positively associated with the proportion of the population with low wealth index (OR: 1.01; 95%CI: 1.0, 1.01), the proportion of the population with poor knowledge about TB (OR: 1.02; 95%CI: 1.01, 1.03), and higher annual mean temperature per degree Celsius (OR: 1.15; 95% CI: 1.08, 1.21).

CONCLUSIONS

This study showed significant spatial variation in poor TB treatment outcomes in Ethiopia that was related to underlying socioeconomic status, knowledge about TB, and climatic conditions. Clinical and public health interventions should be targeted in hot spot areas to reduce poor TB treatment outcomes and to achieve the national End-TB Strategy targets.

Geospatial intelligence and health analitycs: Its application and utility in a city with high tuberculosis incidence in Brazil

BACKGROUND

Geospatial Intelligence and Health Analysis have been used to identify tuberculosis (TB) hotspots and to better understand their relationship to social and economic factors. The purpose of this study was to use geospatial intelligence to assess the distribution of TB and its correlations with Human Development Index (HDI) in a city with high TB incidence in Brazil.

METHODS

We conducted an ecological study, using National System of Information on Noticeable Disease (SINAN) to identify TB cases. Geocoding was performed using QGIS 2.0 software and Google Maps API 3.0. We applied geospatial intelligence to detect where in the city clustering of TB cases occurred, and assessed the association of an area's HDI (each one of the components - longevity, education, and income) with TB spatial distribution.

RESULTS

During the study period (2011-2013), there were 737 TB cases. TB cases showed heterogeneity across the 29 neighborhoods. The neighborhoods with HDI-income lower than the mean had higher TB incidence (p = 0.036).

CONCLUSIONS

We found several hotspots of TB across the 29 neighborhoods, and an inverse association between HDI-income and TB incidence. These findings provide useful information and may help to guide TB control programs.

Analysis on spatial-temporal distribution characteristics of smear positive pulmonary tuberculosis in China, 2004-2015

BACKGROUND

In China, tuberculosis (TB) is still a major infectious disease threatening people's health. Smear positive pulmonary TB is one of the most common infectious forms of TB and it might easily cause the outbreak in some areas. With a better understanding of the spatial-temporal variations of smear positive PTB, we would reach the targets for TB prevention and controlling, identify high-risk areas and periods. Thus, the aim of this study was to investigate the spatial-temporal variations of smear positive PTB.

METHODS

Provincial level data of reported smear positive PTB monthly cases and incidence from January 2004 to December 2015 were obtained from the National Scientific Data Sharing Platform for Population and Health of China. Purely spatial-temporal descriptive analysis was used to characterize the distribution patterns of smear positive PTB. The global spatial auto-correlation statistics (Moran's I) and the local indicators of spatial association (LISA) were conducted to identify the spatial auto-correlation and high risk areas of smear positive PTB cases. Furthermore, the space-time scan statistic was adopted to detect the spatial-temporal clusters in different periods.

RESULTS

A total of 4,711,571 smear positive PTB cases were notified in China with an average annual incidence of 29.59/100,000. The proportion of male in different age groups were obviously higher than that of women. The largest number of cases was reported in the 20-24 years age group. Time-series analysis indicated that monthly incidence appeared a clearly seasonality and periodicity, which the seasonal peaks occurred in January and March. Smear positive PTB cases had a positive global spatial auto-correlation in 2013-2015 (Moran's I=0.186, P=0.046). Spatial clusters were identified in four periods, located in the different regions. The time period of 2004-2006, the most likely spatial-temporal cluster (RR=1.69, P<0.001) was mainly located in Hubei, Hunan, Jiangxi and Anhui of central China, clustering in the time frame from January 2005 to June 2006. During 2007-2009, the most likely spatial-temporal cluster (RR=5.65, P<0.001) was located in Guizhou, clustering in the time frame from January to December 2009. The spatial-temporal clustering in the years 2010-2012 showed the most likely cluster (RR=1.44, P<0.001) was distributed in Anhui, Hunan, Hubei, Jiangxi and Guangdong with the time frame from January 2010 to June 2011. During 2013-2015, the most likely cluster (RR=1.86, P<0.001) was detected in Hunan, Hubei, Jiangxi and Guangdong from February 2013 to June 2014.

CONCLUSIONS

This study identified the spatial-temporal patterns of smear positive PTB in China and demonstrated the capability and utility of the spatial-temporal approach in epidemiology. The results of this study would contribute to estimating the high risk periods and areas, and to providing more useful information for policy-making.

Medication Event Monitoring System for Infectious Tuberculosis Treatment in Morocco: A Retrospective Cohort Study

Non-adherence to tuberculosis (TB) treatment is a barrier to effective TB control. We investigated the effectiveness of a Medication Event Monitoring System (MEMS) as a tailored adherence-promoting intervention in Morocco. We compared patients who received a MEMS (n = 206) with patients who received standard TB care (n = 141) among new active TB patients with sputum smear-positive. The mean total medication days were 141.87 ± 29.5 in the control group and 140.85 ± 17.9 in the MEMS group (p = 0.7147), and the mean age and sex were not different between the two groups (p > 0.05). The treatment success rate was significantly higher in the MEMS group than in the control group (odds ratio (OR): 4.33, 95% confidence interval (CI): 2.13–8.81, p < 0.001), and the lost to follow-up rate was significantly lower in the MEMS group than in the control group (OR: 0.03, 95% CI: 0.05–0.24, p < 0.001) after adjusting for sex, age, and health centers. The mean drug adherence rate in the first month was significantly higher in the MEMS group than in the control group (p = 0.023). MEMS increased TB treatment success rate and decreased the lost to follow-up rate overall for infectious TB patients in a Moroccan rural area.

Optimizing community screening for tuberculosis: Spatial analysis of localized case finding from door-to-door screening for TB in an urban district of Ho Chi Minh City, Viet Nam

BACKGROUND

Tuberculosis (TB) is the deadliest infectious disease globally. Current case finding approaches may miss many people with TB or detect them too late.

DATA AND METHODS

This study was a retrospective, spatial analysis of routine TB surveillance and cadastral data in Go Vap district, Ho Chi Minh City. We geocoded TB notifications from 2011 to 2015 and calculated theoretical yields of simulated door-to-door screening in three concentric catchment areas (50m, 100m, 200m) and three notification window scenarios (one, two and four quarters) for each index case. We calculated average yields, compared them to published reference values and fit a GEE (Generalized Estimating Equation) linear regression model onto the data.

RESULTS

The sample included 3,046 TB patients. Adjusted theoretical yields in 50m, 100m and 200m catchment areas were 0.32% (95%CI: 0.27,0.37), 0.21% (95%CI: 0.14,0.29) and 0.17% (95%CI: 0.09,0.25), respectively, in the baseline notification window scenario. Theoretical yields in the 50m-catchment area for all notification window scenarios were significantly higher than a reference yield from literature. Yield was positively associated with treatment failure index cases (beta = 0.12, p = 0.001) and short-term inter-province migrants (beta = 0.06, p = 0.022), while greater distance to the DTU (beta = -0.02, p<0.001) was associated with lower yield.

CONCLUSIONS

This study is an example of inter-departmental collaboration and application of repurposed cadastral data to progress towards the end TB objectives. The results from Go Vap showed that the use of spatial analysis may be able to identify areas where targeted active case finding in Vietnam can help improve TB case detection.

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.

Spatial data analysis and the use of maps in scientific health articles

INTRODUCTION

Despite the growing number of studies with a characteristic element of spatial analysis, the application of the techniques is not always clear and its continuity in epidemiological studies requires careful evaluation.

OBJECTIVE

To verify the spread and use of those processes in national and international scientific papers.

METHOD

An assessment was made of periodicals according to the impact index. Among 8,281 journals surveyed, four national and four international were selected, of which 1,274 articles were analyzed regarding the presence or absence of spatial analysis techniques.

RESULTS

Just over 10% of articles published in 2011 in high impact journals, both national and international, showed some element of geographical location.

CONCLUSION

Although these percentages vary greatly from one journal to another, denoting different publication profiles, we consider this percentage as an indication that location variables have become an important factor in studies of health.