Assessment of tuberculosis spatial hotspot areas in Antananarivo, Madagascar, by combining spatial analysis and genotyping

Complexities and benefits of adopting next-generation sequencing-based tuberculosis diagnostics: a qualitative study among stakeholders in low and high-income countries

OBJECTIVES

To clarify perceived benefits, barriers and facilitators of Mycobacterium tuberculosis next-generation sequencing implementation in Madagascar and Canada, towards informing implementation of this diagnostic technology in public health agencies and clinical settings in and beyond these settings.

DESIGN

This qualitative study involved conducting semistructured interviews with key stakeholders engaged with next-generation sequencing implementation in Madagascar and Canada. Team-based descriptive analysis supported by Nvivo V.12.0 was used to identify key themes.

SETTING

The study was conducted with participants involved at the clinical, diagnostic and surveillance levels of tuberculosis (TB) management from Madagascar and Canada.

PARTICIPANTS

Eighteen participants were interviewed (nine Madagascar and nine Canada) and included individuals purposively sampled based on involvement with TB surveillance, laboratory diagnosis and clinical management.

RESULTS

The following five themes emerged in the analysis of Malagasy and Canadian interviews: (1) heterogeneity in experience with established TB diagnostics, (2) variable understanding of new sequencing-based diagnostics potential; (3) further evidence as being key to expand adoption; (4) ethical arguments and concerns; (5) operational and system-level considerations.

CONCLUSION

There persists important lack of familiarity with TB next-generation sequencing (TB NGS) applications among stakeholders in Canada and Madagascar. This translates into skepticism on the evidence underlying its use and its true potential value added within global public health systems. If deployed, TB NGS testing should be integrated with clinical and surveillance programmes. Although this is perceived as a priority, leadership and funding responsibilities for this integration to happen remains unclear to clinical, laboratory and public health stakeholders.

Analysis of bluetongue disease epizootics in sheep of Andhra Pradesh, India using spatial and temporal autocorrelation

Bluetongue (BT) disease poses a constant risk to the livestock population around the world. A better understanding of the risk factors will enable a more accurate prediction of the place and time of high-risk events. Mapping the disease epizootics over a period in a particular geographic area will identify the spatial distribution of disease occurrence. A Geographical Information System (GIS) based methodology to analyze the relationship between bluetongue epizootics and spatial-temporal patterns was used for the years 2000 to 2015 in sheep of Andhra Pradesh, India. Autocorrelation (ACF), partial autocorrelation (PACF), and cross-correlation (CCF) analyses were carried out to find the self-dependency between BT epizootics and their dependencies on environmental factors and livestock population. The association with climatic or remote sensing variables at different months lag, including wind speed, temperature, rainfall, relative humidity, normalized difference vegetation index (NDVI), normalized difference water index (NDWI), land surface temperature (LST), was also examined. The ACF & PACF of BT epizootics with its lag showed a significant positive autocorrelation with a month's lag (r = 0.41). Cross-correlations between the environmental variables and BT epizootics indicated the significant positive correlations at 0, 1, and 2 month's lag of rainfall, relative humidity, normalized difference water index (NDWI), and normalized difference vegetation index (NDVI). Spatial autocorrelation analysis estimated the univariate global Moran's I value of 0.21. Meanwhile, the local Moran's I value for the year 2000 (r = 0.32) showed a high degree of spatial autocorrelation. The spatial autocorrelation analysis revealed that the BT epizootics in sheep are having considerable spatial association among the outbreaks in nearby districts, and have to be taken care of while making any forecasting or disease prediction with other risk factors.

Multi Drug Resistant Tuberculosis Clusters in Mpumalanga Province, South Africa, 2013-2016: A Spatial Analysis

OBJECTIVE

To identify spatial clusters with unusually high levels of MDR-TB which are highly unlikely to have arisen by chance in Mpumalanga Province, South Africa.

METHODS

Home addresses of all MDR-TB patients were collected from four MDR-TB facilities from 2013 to 2016. We mapped all addresses, linking them to the nearest ward with population estimates. A spatial analysis was conducted using kernel density in ArcGIS to estimate and map the distribution of the disease and used Gertis-Ord Gi to test for significant clustering.

RESULTS

A total of 4,065 MDR-TB patients were mapped. Ten significant clusters (p-value < 0.05) were found across the province in six sub-districts: Mbombela, Nkomazi, Emalahleni, Govan Mbeki, Lekwa and Mkhondo. Mbombela has the highest number of significant clusters. The central region did not have any MDR-TB clusters.

CONCLUSION

There is clear evidence of MDR-TB clustering in Mpumalanga. This calls for concentrated TB prevention efforts and proper allocation of resources. Further investigations are needed to identify MDR-TB predictors.

Identification of TB space-time clusters and hotspots in Ouest département, Haiti, 2011-2016

BACKGROUND

Haiti has the highest incidence rate of TB in the Western Hemisphere, with an estimated 170 cases per 100,000 in 2019. Since 2010, control efforts have focused on targeted case-finding activities in urban areas, implementation of rapid molecular diagnostics at high-volume TB centers, and improved reporting. TB analyses are rarely focused on lower geographic units; thus, the major goal was to determine if there were focal areas of TB transmission from 2011 to 2016 at operational geographic levels useful for the National TB Control Program (PNLT).

METHODS

We created a geocoder to locate TB cases at the smallest geographic level. Kulldorff's space-time permutation scan, Anselin Moran's I, and Getis-Ord Gi* statistics were used to determine the spatial distribution and clusters of TB.

RESULTS

With 91% of cases linked using the geocoder, TB clusters were identified each year. Getis-Ord Gi* analysis revealed 14 distinct spatial clusters of high incidences in the Port-au-Prince metropolitan area. One hundred retrospective space-time clusters were detected.

CONCLUSION

Our study confirms the presence of TB hotspots in the Ouest département, with most clusters in the Port-au-Prince metropolitan area. Results will help the PNLT and its partners better design case-finding strategies for these areas.

Multidrug-resistant tuberculosis surveillance and cascade of care in Madagascar: a five-year (2012-2017) retrospective study

BACKGROUND

In Madagascar, the multidrug-resistant tuberculosis (MDR-TB) surveillance programme was launched in late 2012 wherein previously treated TB cases and symptomatic MDR-TB contacts (hereafter called presumptive MDR-TB cases) undergo drug susceptibility testing. This retrospective review had per aim to provide an update on the national MDR-TB epidemiology, assess and enhance programmatic performance and assess Madagascar's MDR-TB cascade of care.

METHODS

For 2012-2017, national TB control programme notification, clinical management data and reference laboratory data were gathered. The development and coverage of the surveillance programme, the MDR-TB epidemiology and programmatic performance indicators were assessed using descriptive, logistic and spatial statistical analyses. Data for 2017 was further used to map Madagascar's TB and MDR-TB cascade of care.

RESULTS

The geographical coverage and diagnostic and referral capacities of the MDR-TB surveillance programme were gradually expanded whereas regional variations persist with regard to coverage, referral rates and sample referral delays. Overall, the rate of MDR-TB among presumptive MDR-TB cases remained relatively stable, ranging between 3.9% in 2013 and 4.4% in 2017. Most MDR-TB patients were lost in the second gap of the cascade pertaining to MDR-TB cases reaching diagnostic centres but failing to be accurately diagnosed (59.0%). This poor success in diagnosis of MDR-TB is due to both the current use of low-sensitivity smear microscopy as a first-line diagnostic assay for TB and the limited access to any form of drug susceptibility testing. Presumptive MDR-TB patients' sample referral took a mean delay of 28 days before testing. Seventy-five percent of diagnosed MDR-TB patients were appropriately initiated on treatment, and 33% reached long-term recurrence-free survival.

CONCLUSIONS

An expansion of the coverage and strengthening of MDR-TB diagnostic and management capacities are indicated across all regions of Madagascar. With current limitations, the surveillance programme data is likely to underestimate the true MDR-TB burden in the country and an updated national MDR-TB prevalence survey is warranted. In absence of multiple drivers of an MDR-TB epidemic, including high MDR-TB rates, high HIV infection rates and inter-country migration, Madagascar is in a favourable starting position for MDR-TB control and elimination.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Exploring the usefulness of molecular epidemiology of tuberculosis in Africa: a systematic review

BACKGROUND

Tuberculosis (TB) is caused by Mycobacterium tuberculosis complex (MTBC) and remains a serious global public health threat, especially in resource-limited settings such as the African region. Recent developments in molecular epidemiology tools have significantly improved our understanding of TB transmission patterns and revealed the high genetic diversity of TB isolates across geographical entities in Africa. This study reports the results of a systematic review of current knowledge about MTBC strain diversity and geographical distribution in African regions.

METHODS

Search tools (PubMed, Embase, Popline, OVID and Africa Wide Information) were employed to identify the relevant literature about prevalence, strain diversity, and geographic distribution of MTBC infection in Africa.

RESULTS

A total of 59 articles from 739 citations met our inclusion criteria. Most articles reported about patients with presumptive pulmonary TB (73%), fewer reports were on retreatment and treatment failure cases (12%), and presumptive drug resistance cases (3%). Spoligotyping was the most used, alone in 21 studies and in parallel with either the Mycobacterial Interspersed Repetitive Units Variable Number of Tandem Repeats or the Restriction Fragment Length Polymorphism. Various TB lineages were observed across the African continent, with the originally European lineage 4 spotted in all countries studied.

CONCLUSION

TB molecular epidemiology tools have substantially improved our understanding of the MTBC circulating isolates, their evolution, and diversity in this highly endemic region of Africa. We found that only TB lineage 4 is present throughout all the continent and the clusters identified provides an extended insight into the disease transmission dynamics.

Concurrent adult pulmonary tuberculosis prevalence survey using digital radiography and Xpert MTB/RIF Ultra and child interferon-gamma release assay Mycobacterium tuberculosis infection survey in Karachi, Pakistan: a study protocol

Background: Assessment of the effectiveness of tuberculosis control strategies requires the periodic measurement of M. tuberculosis transmission in populations, which is notoriously difficult. One well-established method is to measure the prevalence of infectious pulmonary tuberculosis in the population which is then repeated at a second time point after a period of 'intervention', such as scale up of the Search-Treat-Prevent strategy of the Zero TB Cities initiative, allowing for a 'before and after' comparison.  Protocol: The concurrent adult pulmonary tuberculosis prevalence survey (using digital radiography and Xpert MTB/RIF Ultra) and child M. tuberculosis infection survey (using QuantiFERON-TB® Gold Plus) will primarily provide a baseline measure of the burden of adult infectious tuberculosis in Karachi and assess whether a large-scale interferon gamma release assay survey in children aged 2 to 4 years is feasible. The target population for the prevalence survey is comprised of a stratified random sample of all adults aged 15 years and above and all children aged 2 to 4 years resident in four districts in Karachi. The survey procedures and analyses to estimate pulmonary tuberculosis prevalence are based on the World Health Organization methodology for tuberculosis prevalence surveys. Ethics and dissemination: The study protocol has been approved by the Interactive Research Development / The Indus Hospital Research Centre Research Ethics Committee in Karachi, Pakistan and the London School of Hygiene & Tropical Medicine Research Ethics Committee. Due to non-representative sampling in this setting, where a large proportion of the population are illiterate and are reluctant to provide fingerprints due to concerns about personal security, verbal informed consent will be obtained from each eligible participant or guardian. Results will be submitted to international peer-reviewed journals, presented at international conferences and shared with participating communities and with the Provincial and National TB programme.

Risk analysis of African swine fever in Poland based on spatio-temporal pattern and Latin hypercube sampling, 2014-2017

Background

African swine fever (ASF) is a devastating infectious disease of pigs. ASF poses a potential threat to the world pig industry, due to the lack of vaccines and treatments. In this study, the Geographic Information System (GIS) spatial analysis was applied to analyze the distribution, dispersion of the epidemic and clustering of ASF in Poland.

Results

The results show that the center of the epidemic moved gradually towards the southwest, and the distribution of the epidemic changed from south-north to east-west. Through space-time scan statistical analysis, the 3 clusters major of wild boar cases involve longer time spans and larger radii, while the other five with higher relative risks involved in domestic pigs. And then, a quantitative model was constructed to analyse the risk of releasing African swine fever virus (ASFV) from Poland by the legal export of pork and pork products. The Latin hypercube sampling results show that the probability is relatively low (the average value is 4.577 × 10^− 7).

Conclusions

All the identification of the spatio-temporal patterns of the epidemic and the risk analysis model would give a further understanding of the dynamics of disease transmission and help to design corresponding measures to minimize the catastrophic consequences of potential ASFV introduction.

Perceptions of drones, digital adherence monitoring technologies and educational videos for tuberculosis control in remote Madagascar: a mixed-method study protocol

INTRODUCTION

Poor road and communication infrastructure pose major challenges to tuberculosis (TB) control in many regions of the world. TB surveillance and patient support often fall to community health workers (CHWs) who may lack the time or knowledge needed for this work. To meet the End TB Strategy goal of reducing TB incidence by 90% by 2035, the WHO calls for intensified research and innovation including the rapid uptake of new tools, interventions and strategies. Technologies that 'leapfrog' infrastructure challenges and support CHWs in TB control responsibilities have the potential to dramatically change TB outcomes in remote regions. Such technologies may strengthen TB control activities within challenged national tuberculosis treatment and control programmes (NTPs), and be adapted to address other public health challenges. The deployment of innovative technologies needs to be differentially adapted to context-specific factors. The Drone Observed Therapy System (DrOTS) project was launched in Madagascar in 2017 and integrates a bundle of innovative technologies including drones, digital adherence monitoring technology and mobile device-based educational videos to support TB control.

METHODS AND ANALYSIS

This mixed-methods study gathers and analyses cultural perceptions of the DrOTS project among key stakeholders: patients, community members, CHWs, village chiefs and NTP-DrOTS mobile health teams. Data from questionnaires, semistructured interviews, focus group discussions (FGD) and ethnographic observation gathered from June 2018 to June 2019 are thematically analysed and compared to identify patterns and singularities in how DrOTS stakeholders perceive and interact with DrOTS technologies, its enrolment processes, objectives and team.

ETHICS AND DISSEMINATION

Ethics approval was obtained from the National Bioethics Research Committee of Madagascar and Stony Brook University institutional review board. Study results will be submitted for peer-reviewed publication. In Madagascar, results will be presented in person to Ministry and other Malagasy decision-makers through the Institut Pasteur de Madagascar.

PATIENT AND PUBLIC INVOLVEMENT

This study is designed to foreground the voices of patients and potential patients in the DrOTS programme. CHW participants in this study also supported the design of study information sessions and recruitment strategies. One member of the mobile health team provided detailed input on the wording and content of FGD and interview guides. Study findings will be presented via a report in French and Malagasy to CHW, mobile health team and other village-level participants who have email/internet access.

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.

Epidemiology and spatial distribution of bluetongue virus in Xinjiang, China

Bluetongue (BT) is a non-contagious disease affecting domestic and wild ruminants. Outbreaks of BT can cause serious economic losses. To investigate the distribution characteristics of bluetongue virus (BTV), two large-scale censuses of BTV prevalence in Xinjiang, China were collected. Spatial autocorrelation analysis, including global spatial autocorrelation and local spatial autocorrelation, was performed. Risk areas for BTV occurrence in Xinjiang were detected using the presence-only maximum entropy model. The global spatial autocorrelation of BTV distribution in Xinjiang in 2012 showed a random pattern. In contrast, the spatial distribution of BTV from 2014 to 2015 was significantly clustered. The hotspot areas for BTV infection included Balikun County (p < 0.05), Yiwu County (p < 0.05) and Hami City (p < 0.05) in 2012. These three regions were also hotspot areas during 2014 and 2015. Sheep distribution (25.6% contribution), precipitation seasonality (22.1% contribution) and mean diurnal range (16.2% contribution) were identified as the most important predictors for BTV occurrence in Xinjiang. This study demonstrated the presence of high-risk areas for BTV infection in Xinjiang, which can serve as a tool to aid in the development of preventative countermeasures of BT outbreaks.

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.

Spatial Patterns and Risk Factors of Bluetongue Virus Infection in Inner Mongolia, China

Bluetongue (BT) is a noncontagious disease affecting domestic and wild ruminants. Outbreaks of BT can cause serious economic losses. Although the causative agent, BT virus (BTV) is endemic in China, a comprehensive analysis has yet to be conducted examining the spatial distribution and risk factors of the virus throughout the Inner Mongolia province. Between June 2013 and February 2015, a total of 6199 blood samples of goats and sheep were collected from 11 leagues and cities. To investigate the distribution characteristics of BTV, spatial autocorrelation analysis, including both global and local spatial autocorrelation, was conducted. To develop a model for the association between BTV infection and specific risk factors, a multiple logistic regression analysis was performed. The global spatial autocorrelation data on the distribution of BTV exhibited a random pattern. Alashan was observed to be a cold spot for BTV infection. During the study period, no hot spots were detected. An increased risk of BTV infection in Inner Mongolia was associated with the breed and age of the animal.

Spatial pattern of foot-and-mouth disease in animals in China, 2010-2016

Foot-and-mouth disease (FMD) is a highly contagious disease of cloven-hoofed animals. An outbreak of FMD can produce devastating economic losses for a considerable length of time. In order to investigate the distribution characteristics of FMD in China, data from 2010 to 2016 were collected, including information on 65 outbreaks of FMD (25 by serotype A and 40 by serotype O), and 5,937 diseased animals (1,691 serotype A and 4,284 serotype O cases). Spatial autocorrelation, including global spatial autocorrelation and local spatial autocorrelation, as well as directional distribution analysis, were performed. Global spatial autocorrelation analysis of FMD cases from 2010 to 2016 did not show clustering (P > 0.05). In 2013 and 2014, the FMD serotype A hotspots areas were Tibet (Z = 3.3236, P < 0.001 in 2013; Z = 3.2001, P < 0.001 in 2014) and Xinjiang provinces (Z = 4.2113, P < 0.001 in 2013; Z = 3.9888, P < 0.001 in 2014). The FMD serotype O hotspots areas were: Xinjiang (Z = 2.5832, P = 0.0098) province in 2010; Tibet (Z = 3.8814, P < 0.001) and Xinjiang (Z = 4.9128, P < 0.001) provinces in 2011; and Tibet (Z = 3.0838, P = 0.0020), Xinjiang (Z = 3.8705, P < 0.001) and Qinghai (Z = 2.8875, P = 0.0039) provinces in 2013. The distribution of FMD cases from 2010 to 2016 showed a significant directional trend (northwest-southeast). In conclusion, our findings revealed the spatial patterns of FMD cases, which may provide beneficial information for the prevention and control of FMD.