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

ABSTRACT: Tuberculosis (TB) remains a public health problem in Madagascar. A crucial element of TB control is the development of an easy and rapid method for the orientation of TB control strategies in the country. Our main objective was to develop a TB spatial hotspot identification method by combining spatial analysis and TB genotyping method in Antananarivo.Sputa of new pulmonary TB cases from 20 TB diagnosis and treatment centers (DTCs) in Antananarivo were collected from August 2013 to May 2014 for culture. Mycobacterium tuberculosis complex (MTBC) clinical isolates were typed by spoligotyping on a Luminex® 200 platform. All TB patients were respectively localized according to their neighborhood residence and the spatial distribution of all pulmonary TB patients and patients with genotypic clustered isolates were scanned respectively by the Kulldorff spatial scanning method for identification of significant spatial clustering. Areas exhibiting spatial clustering of patients with genotypic clustered isolates were considered as hotspot TB areas for transmission.Overall, 467 new cases were included in the study, and 394 spoligotypes were obtained (84.4%). New TB cases were distributed in 133 of the 192 Fokontany (administrative neighborhoods) of Antananarivo (1 to 15 clinical patients per Fokontany) and patients with genotypic clustered isolates were distributed in 127 of the 192 Fokontany (1 to 13 per Fokontany). A single spatial focal point of epidemics was detected when ignoring genotypic data (p = 0.039). One Fokontany of this focal point and three additional ones were detected to be spatially clustered when taking genotypes into account (p < 0.05). These four areas were declared potential TB transmission hotspots in Antananarivo and will be considered as priority targets for surveillance in the future.This method, combining spatial analysis and TB genotyping will now be used for further focused clinical and epidemiological studies in Madagascar and will allow better TB control strategies by public health authorities.

SUBMITTER: Ratovonirina NH

PROVIDER: S-EPMC5557477 | biostudies-other | 2017 Aug

REPOSITORIES: biostudies-other

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Project description:Genetic analysis of pathogenic organisms is a useful tool for linking human cases together and/or to potential environmental sources. The resulting data can also provide information on evolutionary patterns within a targeted species and phenotypic traits. However, the instruments often used to generate genotyping data, such as single nucleotide polymorphisms (SNPs), can be expensive and sometimes require advanced technologies to implement. This places many genotyping tools out of reach for laboratories that do not specialize in genetic studies and/or lack the requisite financial and technological resources. To address this issue, we developed a low cost and low tech genotyping system, termed agarose-MAMA, which combines traditional PCR and agarose gel electrophoresis to target phylogenetically informative SNPs.To demonstrate the utility of this approach for generating genotype data in a resource-constrained area (Madagascar), we designed an agarose-MAMA system targeting previously characterized SNPs within Yersinia pestis, the causative agent of plague. We then used this system to genetically type pathogenic strains of Y. pestis in a Malagasy laboratory not specialized in genetic studies, the Institut Pasteur de Madagascar (IPM). We conducted rigorous assay performance validations to assess potential variation introduced by differing research facilities, reagents, and personnel and found no difference in SNP genotyping results. These agarose-MAMA PCR assays are currently employed as an investigative tool at IPM, providing Malagasy researchers a means to improve the value of their plague epidemiological investigations by linking outbreaks to potential sources through genetic characterization of isolates and to improve understanding of disease ecology that may contribute to a long-term control effort.The success of our study demonstrates that the SNP-based genotyping capacity of laboratories in developing countries can be expanded with manageable financial cost for resource constraint laboratories. This is a practical formula that reduces resource-driven limitations to genetic research and promises to advance global collective knowledge of infectious diseases emanating from resource limited regions of the world.

Project description:The importance of ecosystems for supporting human well-being is increasingly recognized by both the conservation and development sectors. Our ability to conserve ecosystems that people rely on is often limited by a lack of spatially explicit data on the location and distribution of ecosystem services (ES), the benefits provided by nature to people. Thus there is a need to map ES to guide conservation investments, to ensure these co-benefits are maintained. To target conservation investments most effectively, ES assessments must be rigorous enough to support conservation planning, rapid enough to respond to decision-making timelines, and often must rely on existing data. We developed a framework for rapid spatial assessment of ES that relies on expert and stakeholder consultation, available data, and spatial analyses in order to rapidly identify sites providing multiple benefits. We applied the framework in Madagascar, a country with globally significant biodiversity and a high level of human dependence on ecosystems. Our objective was to identify the ES co-benefits of biodiversity priority areas in order to guide the investment strategy of a global conservation fund. We assessed key provisioning (fisheries, hunting and non-timber forest products, and water for domestic use, agriculture, and hydropower), regulating (climate mitigation, flood risk reduction and coastal protection), and cultural (nature tourism) ES. We also conducted multi-criteria analyses to identify sites providing multiple benefits. While our approach has limitations, including the reliance on proximity-based indicators for several ES, the results were useful for targeting conservation investments by the Critical Ecosystem Partnership Fund (CEPF). Because our approach relies on available data, standardized methods for linking ES provision to ES use, and expert validation, it has the potential to quickly guide conservation planning and investment decisions in other data-poor regions.

Project description:BackgroundGenotyping and georeferencing in tuberculosis (TB) have been used to characterize the distribution of the disease and occurrence of transmission within specific groups and communities.ObjectiveThe objective of this study was to test the hypothesis that diabetes mellitus (DM) and pulmonary TB may occur in spatial and molecular aggregations.Material and methodsRetrospective cohort study of patients with pulmonary TB. The study area included 12 municipalities in the Sanitary Jurisdiction of Orizaba, Veracruz, México. Patients with acid-fast bacilli in sputum smears and/or Mycobacterium tuberculosis in sputum cultures were recruited from 1995 to 2010. Clinical (standardized questionnaire, physical examination, chest X-ray, blood glucose test and HIV test), microbiological, epidemiological, and molecular evaluations were carried out. Patients were considered "genotype-clustered" if two or more isolates from different patients were identified within 12 months of each other and had six or more IS6110 bands in an identical pattern, or < 6 bands with identical IS6110 RFLP patterns and spoligotype with the same spacer oligonucleotides. Residential and health care centers addresses were georeferenced. We used a Jeep hand GPS. The coordinates were transferred from the GPS files to ArcGIS using ArcMap 9.3. We evaluated global spatial aggregation of patients in IS6110-RFLP/ spoligotype clusters using global Moran´s I. Since global distribution was not random, we evaluated "hotspots" using Getis-Ord Gi* statistic. Using bivariate and multivariate analysis we analyzed sociodemographic, behavioral, clinic and bacteriological conditions associated with "hotspots". We used STATA® v13.1 for all statistical analysis.ResultsFrom 1995 to 2010, 1,370 patients >20 years were diagnosed with pulmonary TB; 33% had DM. The proportion of isolates that were genotyped was 80.7% (n = 1105), of which 31% (n = 342) were grouped in 91 genotype clusters with 2 to 23 patients each; 65.9% of total clusters were small (2 members) involving 35.08% of patients. Twenty three (22.7) percent of cases were classified as recent transmission. Moran`s I indicated that distribution of patients in IS6110-RFLP/spoligotype clusters was not random (Moran`s I = 0.035468, Z value = 7.0, p = 0.00). Local spatial analysis showed statistically significant spatial aggregation of patients in IS6110-RFLP/spoligotype clusters identifying "hotspots" and "coldspots". GI* statistic showed that the hotspot for spatial clustering was located in Camerino Z. Mendoza municipality; 14.6% (50/342) of patients in genotype clusters were located in a hotspot; of these, 60% (30/50) lived with DM. Using logistic regression the statistically significant variables associated with hotspots were: DM [adjusted Odds Ratio (aOR) 7.04, 95% Confidence interval (CI) 3.03-16.38] and attending the health center in Camerino Z. Mendoza (aOR18.04, 95% CI 7.35-44.28).ConclusionsThe combination of molecular and epidemiological information with geospatial data allowed us to identify the concurrence of molecular clustering and spatial aggregation of patients with DM and TB. This information may be highly useful for TB control programs.

Project description:BackgroundCombining different molecular typing methods for Mycobacterium tuberculosis complex (MTBC) can be a powerful tool for molecular epidemiology-based investigation of TB. However, the current standard method that provides high discriminatory power for such a combination, mycobacterial interspersed repetitive units-variable numbers of tandem repeats typing (MIRU-VNTR), is laborious, time-consuming and often too costly for many resource-limited laboratories. We aimed to evaluate a reduced set of loci for MIRU-VNTR typing in combination with spoligotyping and SNP-typing for routine molecular epidemiology of TB.MethodSpoligotyping and SNP-typing, in combination with the 15 loci MIRU-VNTR typing, were first used to type clinical MTBC isolates (n = 158) from Madagascar. A step by step reduction of MIRU-VNTR loci number was then performed according to the Hunter and Gaston Discriminatory Index (HGDI) and to the Principal component analysis (PCA) correlation with the spoligotype profiles to evaluate the discrimination power inside the generated spoligotype clusters. The 15 MIRU-VNTR was used as reference and SNP-typing was used to determine the main MTBC lineages.ResultsOf the 158 clinical isolates studied, the SNP-typing classified 23 into Lineage 1 (14.6%), 31 into Lineage 2 (19.6%), 23 into Lineage 3 (14.6%) and 81 into Lineage 4 strains (51.3%). 37 different spoligotypes profiles were obtained, 15 of which were unique and 20 in clusters. 15-loci MIRU-VNTR typing revealed 144 different genotypes: 132 isolates had a unique MIRU-VNTR profile and 27 isolates were grouped into 12 clusters. After a stepwise reduction of the MIRU-VNTR loci number within each main spoligotype families, three different sets composed of 5 customised MIRU-VNTR loci had a similar discrimination level to the reference 15 loci MIRU-VNTR in lineage 1, lineage 2 and lineage 3. For lineage 4, a set of 4 and 3 MIRU-VNTR loci were proposed to subtype the Harleem and LAM spoligotype families, respectively. For the T spoligotype family, a set of 5 MIRU-VNTR loci was proposed.ConclusionAccording to the lineages and the spoligotype families, the number of MIRU-VNTR loci can be reduced to get an optimal classification of MTBC. These customized sets of MIRU-VNTR loci reduce workload and save resources while maintaining optimal discriminatory power.

Project description:BackgroundDNA barcoding of non-avian reptiles based on the cytochrome oxidase subunit I (COI) gene is still in a very early stage, mainly due to technical problems. Using a newly developed set of reptile-specific primers for COI we present the first comprehensive study targeting the entire reptile fauna of the fourth-largest island in the world, the biodiversity hotspot of Madagascar.Methodology/principal findingsRepresentatives of the majority of Madagascan non-avian reptile species (including Squamata and Testudines) were sampled and successfully DNA barcoded. The new primer pair achieved a constantly high success rate (72.7-100%) for most squamates. More than 250 species of reptiles (out of the 393 described ones; representing around 64% of the known diversity of species) were barcoded. The average interspecific genetic distance within families ranged from a low of 13.4% in the Boidae to a high of 29.8% in the Gekkonidae. Using the average genetic divergence between sister species as a threshold, 41-48 new candidate (undescribed) species were identified. Simulations were used to evaluate the performance of DNA barcoding as a function of completeness of taxon sampling and fragment length. Compared with available multi-gene phylogenies, DNA barcoding correctly assigned most samples to species, genus and family with high confidence and the analysis of fewer taxa resulted in an increased number of well supported lineages. Shorter marker-lengths generally decreased the number of well supported nodes, but even mini-barcodes of 100 bp correctly assigned many samples to genus and family.Conclusions/significanceThe new protocols might help to promote DNA barcoding of reptiles and the established library of reference DNA barcodes will facilitate the molecular identification of Madagascan reptiles. Our results might be useful to easily recognize undescribed diversity (i.e. novel taxa), to resolve taxonomic problems, and to monitor the international pet trade without specialized expert knowledge.

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

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