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Pando C, Hazel A, Tsang LY, Razafindrina K, Andriamiadanarivo A, Rabetombosoa RM, Ambinintsoa I, Sadananda G, Small PM, Knoblauch AM, Rakotosamimanana N, Grandjean Lapierre S. A social network analysis model approach to understand tuberculosis transmission in remote rural Madagascar. BMC Public Health 2023; 23:1511. [PMID: 37558982 PMCID: PMC10410943 DOI: 10.1186/s12889-023-16425-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 07/31/2023] [Indexed: 08/11/2023] Open
Abstract
BACKGROUND Quality surveillance data used to build tuberculosis (TB) transmission models are frequently unavailable and may overlook community intrinsic dynamics that impact TB transmission. Social network analysis (SNA) generates data on hyperlocal social-demographic structures that contribute to disease transmission. METHODS We collected social contact data in five villages and built SNA-informed village-specific stochastic TB transmission models in remote Madagascar. A name-generator approach was used to elicit individual contact networks. Recruitment included confirmed TB patients, followed by snowball sampling of named contacts. Egocentric network data were aggregated into village-level networks. Network- and individual-level characteristics determining contact formation and structure were identified by fitting an exponential random graph model (ERGM), which formed the basis of the contact structure and model dynamics. Models were calibrated and used to evaluate WHO-recommended interventions and community resiliency to foreign TB introduction. RESULTS Inter- and intra-village SNA showed variable degrees of interconnectivity, with transitivity (individual clustering) values of 0.16, 0.29, and 0.43. Active case finding and treatment yielded 67%-79% reduction in active TB disease prevalence and a 75% reduction in TB mortality in all village networks. Following hypothetical TB elimination and without specific interventions, networks A and B showed resilience to both active and latent TB reintroduction, while Network C, the village network with the highest transitivity, lacked resiliency to reintroduction and generated a TB prevalence of 2% and a TB mortality rate of 7.3% after introduction of one new contagious infection post hypothetical elimination. CONCLUSION In remote Madagascar, SNA-informed models suggest that WHO-recommended interventions reduce TB disease (active TB) prevalence and mortality while TB infection (latent TB) burden remains high. Communities' resiliency to TB introduction decreases as their interconnectivity increases. "Top down" population level TB models would most likely miss this difference between small communities. SNA bridges large-scale population-based and hyper focused community-level TB modeling.
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Affiliation(s)
- Christine Pando
- Stony Brook University, 101 Nicolls Road, Stony Brook, NY, 11794-8343, USA
| | - Ashley Hazel
- Francis I. Proctor Foundation, University of California, San Francisco, 490 Illinois Street, 2nd Floor, San Francisco, CA, 94110, USA
| | - Lai Yu Tsang
- Stony Brook University, 101 Nicolls Road, Stony Brook, NY, 11794-8343, USA
| | | | | | - Roger Mario Rabetombosoa
- Centre ValBio Research Station, BP 33 Ranomafana, Ifanadiana, Madagascar
- Institut Pasteur de Madagascar, 101, Ambohitrakely, Antananarivo, Madagascar
| | - Ideal Ambinintsoa
- Centre ValBio Research Station, BP 33 Ranomafana, Ifanadiana, Madagascar
| | - Gouri Sadananda
- Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH, 44106, USA
| | - Peter M Small
- Stony Brook University, 101 Nicolls Road, Stony Brook, NY, 11794-8343, USA
| | - Astrid M Knoblauch
- Institut Pasteur de Madagascar, 101, Ambohitrakely, Antananarivo, Madagascar
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | | | - Simon Grandjean Lapierre
- Institut Pasteur de Madagascar, 101, Ambohitrakely, Antananarivo, Madagascar.
- Centre de Recherche du Centre Hospitalier de L, Université de Montréal, 900 Saint-Denis, Montréal, H2X 3H8, Canada.
- Université de Montréal, 2900 Edouard Montpetit, Montreal, H3T 1J4, Canada.
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Djibougou DA, Mensah GI, Sagna T, Sawadogo LT, Ouedraogo AK, Kabore A, Hien H, Meda CZ, Combary A, Belem AMG, Addo KK, Dabiré RK, Perreau M, Zinsstag J, Diagbouga SP. Magnitude and associated factors of latent tuberculosis infection due to Mycobacterium tuberculosis complex among high-risk groups in urban Bobo-Dioulasso, Burkina Faso. IJID REGIONS 2022; 4:1-9. [PMID: 36093366 PMCID: PMC9453046 DOI: 10.1016/j.ijregi.2022.05.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 05/09/2022] [Accepted: 05/12/2022] [Indexed: 11/02/2022]
Abstract
The overall prevalence of latent tuberculosis infection (LTBI) in this study was 63.36%. The positivity rate for the tuberculin skin test was higher compared with the QuantiFERON-TB Gold Plus test. The prevalence of LTBI was high among slaughterhouse workers (100%). Protozoal infection was found to be significantly associated with LTBI.
Objectives Methods Results Conclusion
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