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Tuschhoff BM, Kennedy DA. Detecting and quantifying heterogeneity in susceptibility using contact tracing data. PLoS Comput Biol 2024; 20:e1012310. [PMID: 39074159 PMCID: PMC11309420 DOI: 10.1371/journal.pcbi.1012310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 08/08/2024] [Accepted: 07/10/2024] [Indexed: 07/31/2024] Open
Abstract
The presence of heterogeneity in susceptibility, differences between hosts in their likelihood of becoming infected, can fundamentally alter disease dynamics and public health responses, for example, by changing the final epidemic size, the duration of an epidemic, and even the vaccination threshold required to achieve herd immunity. Yet, heterogeneity in susceptibility is notoriously difficult to detect and measure, especially early in an epidemic. Here we develop a method that can be used to detect and estimate heterogeneity in susceptibility given contact by using contact tracing data, which are typically collected early in the course of an outbreak. This approach provides the capability, given sufficient data, to estimate and account for the effects of this heterogeneity before they become apparent during an epidemic. It additionally provides the capability to analyze the wealth of contact tracing data available for previous epidemics and estimate heterogeneity in susceptibility for disease systems in which it has never been estimated previously. The premise of our approach is that highly susceptible individuals become infected more often than less susceptible individuals, and so individuals not infected after appearing in contact networks should be less susceptible than average. This change in susceptibility can be detected and quantified when individuals show up in a second contact network after not being infected in the first. To develop our method, we simulated contact tracing data from artificial populations with known levels of heterogeneity in susceptibility according to underlying discrete or continuous distributions of susceptibilities. We analyzed these data to determine the parameter space under which we are able to detect heterogeneity and the accuracy with which we are able to estimate it. We found that our power to detect heterogeneity increases with larger sample sizes, greater heterogeneity, and intermediate fractions of contacts becoming infected in the discrete case or greater fractions of contacts becoming infected in the continuous case. We also found that we are able to reliably estimate heterogeneity and disease dynamics. Ultimately, this means that contact tracing data alone are sufficient to detect and quantify heterogeneity in susceptibility.
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Affiliation(s)
- Beth M. Tuschhoff
- Department of Biology, The Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - David A. Kennedy
- Department of Biology, The Pennsylvania State University, University Park, Pennsylvania, United States of America
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Rubio FA, Amad AAS, Aransiola TJ, de Oliveira RB, Naidoo M, Moya EMD, Anderle RV, Sironi AP, Ordoñez JA, Sanchez MN, de Oliveira JF, de Souza LE, Dourado I, Macinko J, Rasella D. Evaluating social protection mitigation effects on HIV/AIDS and Tuberculosis through a mathematical modelling study. Sci Rep 2024; 14:11739. [PMID: 38778134 PMCID: PMC11111786 DOI: 10.1038/s41598-024-62007-0] [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: 08/28/2023] [Accepted: 05/13/2024] [Indexed: 05/25/2024] Open
Abstract
The global economic downturn due to the COVID-19 pandemic, war in Ukraine, and worldwide inflation surge may have a profound impact on poverty-related infectious diseases, especially in low-and middle-income countries (LMICs). In this work, we developed mathematical models for HIV/AIDS and Tuberculosis (TB) in Brazil, one of the largest and most unequal LMICs, incorporating poverty rates and temporal dynamics to evaluate and forecast the impact of the increase in poverty due to the economic crisis, and estimate the mitigation effects of alternative poverty-reduction policies on the incidence and mortality from AIDS and TB up to 2030. Three main intervention scenarios were simulated-an economic crisis followed by the implementation of social protection policies with none, moderate, or strong coverage-evaluating the incidence and mortality from AIDS and TB. Without social protection policies to mitigate the impact of the economic crisis, the burden of HIV/AIDS and TB would be significantly larger over the next decade, being responsible in 2030 for an incidence 13% (95% CI 4-31%) and mortality 21% (95% CI 12-34%) higher for HIV/AIDS, and an incidence 16% (95% CI 10-25%) and mortality 22% (95% CI 15-31%) higher for TB, if compared with a scenario of moderate social protection. These differences would be significantly larger if compared with a scenario of strong social protection, resulting in more than 230,000 cases and 34,000 deaths from AIDS and TB averted over the next decade in Brazil. Using a comprehensive approach, that integrated economic forecasting with mathematical and epidemiological models, we were able to show the importance of implementing robust social protection policies to avert a significant increase in incidence and mortality from AIDS and TB during the current global economic downturn.
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Affiliation(s)
- Felipe Alves Rubio
- Institute of Collective Health (ISC), Federal University of Bahia (UFBA), Bahia, Brazil.
- ISGLOBAL, Hospital Clínic-Universitat de Barcelona, Barcelona, Spain.
| | - Alan Alves Santana Amad
- Center for Data and Knowledge Integration for Health, Salvador, Brazil
- College of Engineering, Swansea University, Bay Campus, Swansea, UK
| | | | | | - Megan Naidoo
- ISGLOBAL, Hospital Clínic-Universitat de Barcelona, Barcelona, Spain
| | | | | | - Alberto Pietro Sironi
- Institute of Collective Health (ISC), Federal University of Bahia (UFBA), Bahia, Brazil
| | | | | | | | - Luis Eugenio de Souza
- Institute of Collective Health (ISC), Federal University of Bahia (UFBA), Bahia, Brazil
| | - Inês Dourado
- Institute of Collective Health (ISC), Federal University of Bahia (UFBA), Bahia, Brazil
| | - James Macinko
- Department of Health Policy and Management, University of California, Los Angeles, USA
| | - Davide Rasella
- Institute of Collective Health (ISC), Federal University of Bahia (UFBA), Bahia, Brazil
- ISGLOBAL, Hospital Clínic-Universitat de Barcelona, Barcelona, Spain
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3
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Rafiee M, Jahangiri-Rad M, Mohseni-Bandpei A, Razmi E. Impacts of socioeconomic and environmental factors on neoplasms incidence rates using machine learning and GIS: a cross-sectional study in Iran. Sci Rep 2024; 14:10604. [PMID: 38719879 PMCID: PMC11078954 DOI: 10.1038/s41598-024-61397-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 05/06/2024] [Indexed: 05/12/2024] Open
Abstract
Neoplasm is an umbrella term used to describe either benign or malignant conditions. The correlations between socioeconomic and environmental factors and the occurrence of new-onset of neoplasms have already been demonstrated in a body of research. Nevertheless, few studies have specifically dealt with the nature of relationship, significance of risk factors, and geographic variation of them, particularly in low- and middle-income communities. This study, thus, set out to (1) analyze spatiotemporal variations of the age-adjusted incidence rate (AAIR) of neoplasms in Iran throughout five time periods, (2) investigate relationships between a collection of environmental and socioeconomic indicators and the AAIR of neoplasms all over the country, and (3) evaluate geographical alterations in their relative importance. Our cross-sectional study design was based on county-level data from 2010 to 2020. AAIR of neoplasms data was acquired from the Institute for Health Metrics and Evaluation (IHME). HotSpot analyses and Anselin Local Moran's I indices were deployed to precisely identify AAIR of neoplasms high- and low-risk clusters. Multi-scale geographically weight regression (MGWR) analysis was worked out to evaluate the association between each explanatory variable and the AAIR of neoplasms. Utilizing random forests (RF), we also examined the relationships between environmental (e.g., UV index and PM2.5 concentration) and socioeconomic (e.g., Gini coefficient and literacy rate) factors and AAIR of neoplasms. AAIR of neoplasms displayed a significant increasing trend over the study period. According to the MGWR, the only factor that significantly varied spatially and was associated with the AAIR of neoplasms in Iran was the UV index. A good accuracy RF model was confirmed for both training and testing data with correlation coefficients R2 greater than 0.91 and 0.92, respectively. UV index and Gini coefficient ranked the highest variables in the prediction of AAIR of neoplasms, based on the relative influence of each variable. More research using machine learning approaches taking the advantages of considering all possible determinants is required to assess health strategies outcomes and properly formulate policy planning.
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Affiliation(s)
- Mohammad Rafiee
- Air Quality and Climate Change Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
- Department of Environmental Health Engineering, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mahsa Jahangiri-Rad
- Department of Environmental Health Engineering, School of Health, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran.
- Water Purification Research Center, Islamic Azad University, Tehran, Iran.
| | - Anoushiravan Mohseni-Bandpei
- Air Quality and Climate Change Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
- Department of Environmental Health Engineering, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Elham Razmi
- Department of Environmental Health Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
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Delgado Moya EM, Ordoñez JA, Alves Rubio F, Niskier Sanchez M, de Oliveira RB, Volmir Anderle R, Rasella D. A Mathematical Model for the Impact of 3HP and Social Programme Implementation on the Incidence and Mortality of Tuberculosis: Study in Brazil. Bull Math Biol 2024; 86:61. [PMID: 38662288 DOI: 10.1007/s11538-024-01285-1] [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: 12/08/2023] [Accepted: 03/19/2024] [Indexed: 04/26/2024]
Abstract
In this paper, we presented a mathematical model for tuberculosis with treatment for latent tuberculosis cases and incorporated social implementations based on the impact they will have on tuberculosis incidence, cure, and recovery. We incorporated two variables containing the accumulated deaths and active cases into the model in order to study the incidence and mortality rate per year with the data reported by the model. Our objective is to study the impact of social program implementations and therapies on latent tuberculosis in particular the use of once-weekly isoniazid-rifapentine for 12 weeks (3HP). The computational experimentation was performed with data from Brazil and for model calibration, we used the Markov Chain Monte Carlo method (MCMC) with a Bayesian approach. We studied the effect of increasing the coverage of social programs, the Bolsa Familia Programme (BFP) and the Family Health Strategy (FHS) and the implementation of the 3HP as a substitution therapy for two rates of diagnosis and treatment of latent at 1% and 5%. Based of the data obtained by the model in the period 2023-2035, the FHS reported better results than BFP in the case of social implementations and 3HP with a higher rate of diagnosis and treatment of latent in the reduction of incidence and mortality rate and in cases and deaths avoided. With the objective of linking the social and biomedical implementations, we constructed two different scenarios with the rate of diagnosis and treatment. We verified with results reported by the model that with the social implementations studied and the 3HP with the highest rate of diagnosis and treatment of latent, the best results were obtained in comparison with the other independent and joint implementations. A reduction of the incidence by 36.54% with respect to the model with the current strategies and coverage was achieved, and a greater number of cases and deaths from tuberculosis was avoided.
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Affiliation(s)
- Erick Manuel Delgado Moya
- Institute of Collective Health (ISC), Federal University of Bahia (UFBA), Rua Basilio da Gama, Salvador, Bahia, 40.110-040, Brazil.
| | - Jose Alejandro Ordoñez
- Institute of Collective Health (ISC), Federal University of Bahia (UFBA), Rua Basilio da Gama, Salvador, Bahia, 40.110-040, Brazil
| | - Felipe Alves Rubio
- Institute of Collective Health (ISC), Federal University of Bahia (UFBA), Rua Basilio da Gama, Salvador, Bahia, 40.110-040, Brazil
| | - Mauro Niskier Sanchez
- Institute of Collective Health (ISC), Federal University of Bahia (UFBA), Rua Basilio da Gama, Salvador, Bahia, 40.110-040, Brazil
- Department of Public Health, University of Brasilia, Campus Universitarios Darcy Ribeiro, Brasilia, Brasilia-DF, 70.910900, Brazil
| | - Robson Bruniera de Oliveira
- Institute of Collective Health (ISC), Federal University of Bahia (UFBA), Rua Basilio da Gama, Salvador, Bahia, 40.110-040, Brazil
| | - Rodrigo Volmir Anderle
- Institute of Collective Health (ISC), Federal University of Bahia (UFBA), Rua Basilio da Gama, Salvador, Bahia, 40.110-040, Brazil
| | - Davide Rasella
- Institute of Collective Health (ISC), Federal University of Bahia (UFBA), Rua Basilio da Gama, Salvador, Bahia, 40.110-040, Brazil
- Institute of Global Health (ISGlobal), Barcelona, Spain
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5
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Shrestha S, Mishra G, Hamal M, Dhital R, Shrestha S, Shrestha A, Shah NP, Khanal M, Gurung S, Caws M. Quantifying the potential epidemiological impact of a 2-year active case finding for tuberculosis in rural Nepal: a model-based analysis. BMJ Open 2023; 13:e062123. [PMID: 37914308 PMCID: PMC10626874 DOI: 10.1136/bmjopen-2022-062123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 09/22/2023] [Indexed: 11/03/2023] Open
Abstract
OBJECTIVES Active case finding (ACF) is an important tuberculosis (TB) intervention in high-burden settings. However, empirical evidence garnered from field data has been equivocal about the long-term community-level impact, and more data at a finer geographic scale and data-informed methods to quantify their impact are necessary. METHODS Using village development committee (VDC)-level data on TB notification and demography between 2016 and 2017 in four southern districts of Nepal, where ACF activities were implemented as a part of the IMPACT-TB study between 2017 and 2019, we developed VDC-level transmission models of TB and ACF. Using these models and ACF yield data collected in the study, we estimated the potential epidemiological impact of IMPACT-TB ACF and compared its efficiency across VDCs in each district. RESULTS Cases were found in the majority of VDCs during IMPACT-TB ACF, but the number of cases detected within VDCs correlated weakly with historic case notification rates. We projected that this ACF intervention would reduce the TB incidence rate by 14% (12-16) in Chitwan, 8.6% (7.3-9.7) in Dhanusha, 8.3% (7.3-9.2) in Mahottari and 3% (2.5-3.2) in Makwanpur. Over the next 10 years, we projected that this intervention would avert 987 (746-1282), 422 (304-571), 598 (450-782) and 197 (172-240) cases in Chitwan, Dhanusha, Mahottari and Makwanpur, respectively. There was substantial variation in the efficiency of ACF across VDCs: there was up to twofold difference in the number of cases averted in the 10 years per case detected. CONCLUSION ACF data confirm that TB is widely prevalent, including in VDCs with relatively low reporting rates. Although ACF is a highly efficient component of TB control, its impact can vary substantially at local levels and must be combined with other interventions to alter TB epidemiology significantly.
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Affiliation(s)
- Sourya Shrestha
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Gokul Mishra
- Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, Liverpool, UK
- Birat Nepal Medical Trust, Kathmandu, Nepal
| | - Mukesh Hamal
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | | | | | | | | | | | - Suman Gurung
- Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, Liverpool, UK
- Birat Nepal Medical Trust, Kathmandu, Nepal
| | - Maxine Caws
- Birat Nepal Medical Trust, Kathmandu, Nepal
- Liverpool School of Tropical Medicine, Liverpool, UK
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6
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Quaife M, Medley GF, Jit M, Drake T, Asaria M, van Baal P, Baltussen R, Bollinger L, Bozzani F, Brady O, Broekhuizen H, Chalkidou K, Chi YL, Dowdy DW, Griffin S, Haghparast-Bidgoli H, Hallett T, Hauck K, Hollingsworth TD, McQuaid CF, Menzies NA, Merritt MW, Mirelman A, Morton A, Ruiz FJ, Siapka M, Skordis J, Tediosi F, Walker P, White RG, Winskill P, Vassall A, Gomez GB. Considering equity in priority setting using transmission models: Recommendations and data needs. Epidemics 2022; 41:100648. [PMID: 36343495 PMCID: PMC9623400 DOI: 10.1016/j.epidem.2022.100648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 09/20/2022] [Accepted: 10/21/2022] [Indexed: 11/06/2022] Open
Abstract
OBJECTIVES Disease transmission models are used in impact assessment and economic evaluations of infectious disease prevention and treatment strategies, prominently so in the COVID-19 response. These models rarely consider dimensions of equity relating to the differential health burden between individuals and groups. We describe concepts and approaches which are useful when considering equity in the priority setting process, and outline the technical choices concerning model structure, outputs, and data requirements needed to use transmission models in analyses of health equity. METHODS We reviewed the literature on equity concepts and approaches to their application in economic evaluation and undertook a technical consultation on how equity can be incorporated in priority setting for infectious disease control. The technical consultation brought together health economists with an interest in equity-informative economic evaluation, ethicists specialising in public health, mathematical modellers from various disease backgrounds, and representatives of global health funding and technical assistance organisations, to formulate key areas of consensus and recommendations. RESULTS We provide a series of recommendations for applying the Reference Case for Economic Evaluation in Global Health to infectious disease interventions, comprising guidance on 1) the specification of equity concepts; 2) choice of evaluation framework; 3) model structure; and 4) data needs. We present available conceptual and analytical choices, for example how correlation between different equity- and disease-relevant strata should be considered dependent on available data, and outline how assumptions and data limitations can be reported transparently by noting key factors for consideration. CONCLUSIONS Current developments in economic evaluations in global health provide a wide range of methodologies to incorporate equity into economic evaluations. Those employing infectious disease models need to use these frameworks more in priority setting to accurately represent health inequities. We provide guidance on the technical approaches to support this goal and ultimately, to achieve more equitable health policies.
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Affiliation(s)
- M. Quaife
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, UK,Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, UK
| | - GF Medley
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, UK
| | - M. Jit
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, UK
| | - T. Drake
- Center for Global Development in Europe (CGD Europe), UK
| | - M. Asaria
- LSE Health, London School of Economics, UK
| | - P. van Baal
- Erasmus School of Health Policy & Management, Erasmus University Rotterdam, the Netherlands
| | - R. Baltussen
- Nijmegen International Center for Health Systems Research and Education, Radboudmc, the Netherlands
| | | | - F. Bozzani
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, UK
| | - O. Brady
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, UK
| | - H. Broekhuizen
- Centre for Space, Place, and Society, Wageningen University and Research, Netherlands
| | - K. Chalkidou
- International Decision Support Initiative, Imperial College London, UK
| | - Y.-L. Chi
- International Decision Support Initiative, Imperial College London, UK
| | - DW Dowdy
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, USA
| | - S. Griffin
- Centre for Health Economics, University of York, UK
| | - H. Haghparast-Bidgoli
- Institute for Global Health, Centre for Global Health Economics, University College London, UK
| | - T. Hallett
- Department of Infectious Disease Epidemiology, Imperial College London, UK
| | - K. Hauck
- Department of Infectious Disease Epidemiology, Imperial College London, UK
| | - TD Hollingsworth
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, UK
| | - CF McQuaid
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, UK
| | - NA Menzies
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, USA
| | - MW Merritt
- Johns Hopkins Berman Institute of Bioethics and Department of International Health, Johns Hopkins Bloomberg School of Public Health, United States
| | - A. Mirelman
- Centre for Health Economics, University of York, UK
| | - A. Morton
- Department of Management Science, University of Strathclyde, UK
| | - FJ Ruiz
- International Decision Support Initiative, Imperial College London, UK
| | - M. Siapka
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, UK,Impact Elipsis, Greece
| | - J. Skordis
- Institute for Global Health, Centre for Global Health Economics, University College London, UK
| | - F. Tediosi
- Swiss Tropical and Public Health Institute and Universität Basel, Switzerland
| | - P. Walker
- Department of Infectious Disease Epidemiology, Imperial College London, UK
| | - RG White
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, UK
| | - P. Winskill
- Department of Infectious Disease Epidemiology, Imperial College London, UK
| | - A. Vassall
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, UK,Correspondence to: London School of Hygiene and Tropical Medicine, 15 – 17 Tavistock Place, London WC1H 9SH, UK
| | - GB Gomez
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, UK
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Ayabina DV, Gomes MGM, Nguyen NV, Vo L, Shreshta S, Thapa A, Codlin AJ, Mishra G, Caws M. The impact of active case finding on transmission dynamics of tuberculosis: A modelling study. PLoS One 2021; 16:e0257242. [PMID: 34797864 PMCID: PMC8604297 DOI: 10.1371/journal.pone.0257242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 08/26/2021] [Indexed: 11/18/2022] Open
Abstract
Background In the last decade, active case finding (ACF) strategies for tuberculosis (TB) have been implemented in many diverse settings, with some showing large increases in case detection and reporting at the sub-national level. There have also been several studies which seek to provide evidence for the benefits of ACF to individuals and communities in the broader context. However, there remains no quantification of the impact of ACF with regards to reducing the burden of transmission. We sought to address this knowledge gap and quantify the potential impact of active case finding on reducing transmission of TB at the national scale and further, to determine the intensification of intervention efforts required to bring the reproduction number (R0) below 1 for TB. Methods We adopt a dynamic transmission model that incorporates heterogeneity in risk to TB to assess the impact of an ACF programme (IMPACT TB) on reducing TB incidence in Vietnam and Nepal. We fit the models to country-level incidence data using a Bayesian Markov Chain Monte Carlo approach. We assess the impact of ACF using a parameter in our model, which we term the treatment success rate. Using programmatic data, we estimate how much this parameter has increased as a result of IMPACT TB in the implementation districts of Vietnam and Nepal and quantify additional efforts needed to eliminate transmission of TB in these countries by 2035. Results Extending the IMPACT TB programme to national coverage would lead to moderate decreases in TB incidence and would not be enough to interrupt transmission by 2035. Decreasing transmission sufficiently to bring the reproduction number (R0) below 1, would require a further intensification of current efforts, even at the sub-national level. Conclusions Active case finding programmes are effective in reducing TB in the short term. However, interruption of transmission in high-burden countries, like Vietnam and Nepal, will require comprehensive incremental efforts. Complementary measures to reduce progression from infection to disease, and reactivation of latent infection, are needed to meet the WHO End TB incidence targets.
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Affiliation(s)
- Diepreye Victoria Ayabina
- Liverpool School of Tropical Medicine, Liverpool, United Kingdom
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
- * E-mail:
| | - M. Gabriela M. Gomes
- Liverpool School of Tropical Medicine, Liverpool, United Kingdom
- CIBIO-InBIO, Centro de Investiga¸c˜ao em Biodiversidade e Recursos Gen´eticos, and CMUP, Centro de Matem´atica da Universidade do Porto, Porto, Portugal
| | - Nhung Viet Nguyen
- National Tuberculosis Control Programme of Vietnam- National Lung Hospital (VNTP-NLH), Hanoi, Vietnam
| | - Luan Vo
- Friends for International TB Relief (FIT), Ho Chi Minh City, Vietnam
| | | | - Anil Thapa
- National TB Control Centre, Thimi, Kathmandu, Nepal
| | | | - Gokul Mishra
- Liverpool School of Tropical Medicine, Liverpool, United Kingdom
- Birat Nepal Medical Trust, Kathmandu, Nepal
| | - Maxine Caws
- Liverpool School of Tropical Medicine, Liverpool, United Kingdom
- Birat Nepal Medical Trust, Kathmandu, Nepal
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8
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Maciel ELN, Jabor PM, Macedo LR, Almada GL, Zanotti RL, Cerutti Junior C, Gomes CC, Alencar FECD, Reuter T, Andrade VLGD, Cardoso OA, Medeiros Junior NFD, Bastos WM, Bertolani MN, Silva LT, Zandonade E. Living conditions, seroprevalence and symptoms of COVID-19 in slums in the Metropolitan Region of Vitória (Espírito Santo). REVISTA BRASILEIRA DE EPIDEMIOLOGIA 2021; 24:e210048. [PMID: 34730710 DOI: 10.1590/1980-549720210048] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 08/05/2021] [Indexed: 11/22/2022] Open
Abstract
OBJECTIVES to estimate the prevalence of SARS-CoV-2 infection in residents of the Greater Vitória region living in subnormal and non-subnormal agglomerates, and to compare sociodemographic and clinical characteristics of total residents (infected and not infected with SARS-CoV-2) between them. METHODS Population-based prevalence study conducted by serological testing in 2020, with a study unit in households in Greater Vitória, grouped into census tracts classified as sub-normal agglomerates and non-sub-normal agglomerates. The two groups were compared in terms of prevalence and associated factors. The significance level adopted was 5%. RESULTS The prevalence found in the sub-normal clusters was 12.05% (95%CI 9.59-14.50), and in the non-sub-normal clusters 10.23% (95%CI 7.97-12.50) this difference was not statistically significant (p = 0.273). Comparing the sociodemographic characteristics, more people who declare themselves to be of mixed race were found in the sub-normal clusters, a higher percentage of illiterates and people with only elementary education, greater number of residents per household, longer stay in public transportation, sharing a bathroom with another household, fewer bedrooms per residence and higher frequency of irregular water supply when compared to non-sub-normal clusters (p < 0.05). CONCLUSIONS The epidemiological characteristics of sub-normal clusters' residents show the social inequalities that can hinder control measures in a pandemic situation.
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Affiliation(s)
- Ethel Leonor Noia Maciel
- Biomedical Center, Department of Nursing, Universidade Federal do Espírito Santo - Vitória (ES), Brazil.,Epidemiology Laboratory, Universidade Federal do Espírito Santo - Vitória (ES), Brazil
| | | | - Laylla Ribeiro Macedo
- Epidemiology Laboratory, Universidade Federal do Espírito Santo - Vitória (ES), Brazil
| | | | | | | | | | | | - Tania Reuter
- Universitary hospital Cassiano Antonio de Moraes - Vitória (ES), Brazil
| | | | | | | | | | | | | | - Eliana Zandonade
- Center for Exact Sciences, Universidade Federal do Espírito Santo - Vitória (ES), Brazil
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9
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To Be or to Have Been Lucky, That Is the Question. PHILOSOPHIES 2021. [DOI: 10.3390/philosophies6030057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Is it possible to measure the dispersion of ex ante chances (i.e., chances “before the event”) among people, be it gambling, health, or social opportunities? We explore this question and provide some tools, including a statistical test, to evidence the actual dispersion of ex ante chances in various areas, with a focus on chronic diseases. Using the principle of maximum entropy, we derive the distribution of the risk of becoming ill in the global population as well as in the population of affected people. We find that affected people are either at very low risk, like the overwhelming majority of the population, but still were unlucky to become ill, or are at extremely high risk and were bound to become ill.
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10
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Corder RM, Ferreira MU, Gomes MGM. Modelling the epidemiology of residual Plasmodium vivax malaria in a heterogeneous host population: A case study in the Amazon Basin. PLoS Comput Biol 2020; 16:e1007377. [PMID: 32168349 PMCID: PMC7108741 DOI: 10.1371/journal.pcbi.1007377] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2019] [Revised: 03/31/2020] [Accepted: 01/29/2020] [Indexed: 02/07/2023] Open
Abstract
The overall malaria burden in the Americas has decreased dramatically over the past two decades, but residual transmission pockets persist across the Amazon Basin, where Plasmodium vivax is the predominant infecting species. Current elimination efforts require a better quantitative understanding of malaria transmission dynamics for planning, monitoring, and evaluating interventions at the community level. This can be achieved with mathematical models that properly account for risk heterogeneity in communities approaching elimination, where few individuals disproportionately contribute to overall malaria prevalence, morbidity, and onwards transmission. Here we analyse demographic information combined with routinely collected malaria morbidity data from the town of Mâncio Lima, the main urban transmission hotspot of Brazil. We estimate the proportion of high-risk subjects in the host population by fitting compartmental susceptible-infected-susceptible (SIS) transmission models simultaneously to age-stratified vivax malaria incidence densities and the frequency distribution of P. vivax malaria attacks experienced by each individual over 12 months. Simulations with the best-fitting SIS model indicate that 20% of the hosts contribute 86% of the overall vivax malaria burden. Despite the low overall force of infection typically found in the Amazon, about one order of magnitude lower than that in rural Africa, high-risk individuals gradually develop clinical immunity following repeated infections and eventually constitute a substantial infectious reservoir comprised of asymptomatic parasite carriers that is overlooked by routine surveillance but likely fuels onwards malaria transmission. High-risk individuals therefore represent a priority target for more intensive and effective interventions that may not be readily delivered to the entire community.
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Affiliation(s)
- Rodrigo M. Corder
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil
- * E-mail: (RMC); (MGMG)
| | - Marcelo U. Ferreira
- Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil
| | - M. Gabriela M. Gomes
- Liverpool School of Tropical Medicine, Liverpool, United Kingdom
- CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, and CMUP, Centro de Matemática da Universidade do Porto, Porto, Portugal
- * E-mail: (RMC); (MGMG)
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11
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Reid M, Roberts G, Goosby E, Wesson P. Monitoring Universal Health Coverage (UHC) in high Tuberculosis burden countries: Tuberculosis mortality an important tracer of UHC service coverage. PLoS One 2019; 14:e0223559. [PMID: 31665144 PMCID: PMC6821027 DOI: 10.1371/journal.pone.0223559] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Accepted: 09/23/2019] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND There is a paucity of empiric data evaluating whether Tuberculosis (TB) is a useful surrogate measure for Universal Health Coverage (UHC), despite recognition of the importance of TB control efforts as part of the broader UHC agenda. We hypothesized that indicators of TB burden and coverage are sensitive tracers of UHC, when compared to other disease-specific indicators of service provision. METHODS Linear regression models were used to determine the extent to which variability in UHC Service Coverage Index (SCI) was accounted for by (1) TB incidence rates and (2) TB mortality rates across 183 countries. Dominance analyses, stratifying countries by World Bank income criteria and TB burden, were used to determine the importance of TB treatment coverage in predicting UHC SCI scores, relative to other disease-specific indicators of service provision. RESULTS Across 183 countries, TB incidence rate and TB mortality rate were negatively correlated, with UHC SCI score, (r = -0.67 and r = -0.74, respectively). In linear regression models including all 183 countries, TB incidence rates explained 45% of the variability in SCI scores; TB mortality rate explained 55% of variability. Restricting models to the 30 highest TB burden countries, both incidence and mortality explained less of the variability in SCI score (16% and 36%, respectively). In dominance analysis, comparing 13 disease-specific indicators of service provision, TB effective treatment coverage, ranked ninth overall. In dominance analysis stratified by TB burden, the TB treatment coverage estimate was ranked ninth in the 30 high burden countries and sixth in the 153 non-high burden countries. In separate analyses stratified by world bank income status, TB coverage ranked as third most important variable in LICs and fifth in LMICs and UMICs, but was less important in analysis restricted HICs (ranked seventh). CONCLUSIONS Compared to other disease-specific indicators of service provision, TB coverage was an important indicator of overall UHC service coverage, especially in low-income countries. These findings highlight that national-level inequities in TB-coverage may be an important tracer of universal health coverage.
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Affiliation(s)
- Michael Reid
- University of California, San Francisco, School of Medicine, San Francisco, California, United States of America
- University of California, San Francisco, Institute for Global Health Sciences, San Francisco, California, United States of America
- * E-mail:
| | - Glenna Roberts
- University of California, San Francisco, Institute for Global Health Sciences, San Francisco, California, United States of America
| | - Eric Goosby
- University of California, San Francisco, School of Medicine, San Francisco, California, United States of America
- University of California, San Francisco, Institute for Global Health Sciences, San Francisco, California, United States of America
| | - Paul Wesson
- University of California, San Francisco, School of Medicine, San Francisco, California, United States of America
- University of California, San Francisco, Center of AIDS Prevention Studies, San Francisco, California, United States of America
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12
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Gomes MGM, King JG, Nunes A, Colegrave N, Hoffmann AA. The effects of individual nonheritable variation on fitness estimation and coexistence. Ecol Evol 2019; 9:8995-9004. [PMID: 31462998 PMCID: PMC6706197 DOI: 10.1002/ece3.5437] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Accepted: 06/18/2019] [Indexed: 12/17/2022] Open
Abstract
Demographic theory and data have emphasized that nonheritable variation in individual frailty enables selection within cohorts, affecting the dynamics of a population while being invisible to its evolution. Here, we include the component of individual variation in longevity or viability which is nonheritable in simple bacterial growth models and explore its ecological and evolutionary impacts. First, we find that this variation produces consistent trends in longevity differences between bacterial genotypes when measured across stress gradients. Given that direct measurements of longevity are inevitably biased due to the presence of this variation and ongoing selection, we propose the use of the trend itself for obtaining more exact inferences of genotypic fitness. Second, we show how species or strain coexistence can be enabled by nonheritable variation in longevity or viability. These general conclusions are likely to extend beyond bacterial systems.
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Affiliation(s)
- M. Gabriela M. Gomes
- Liverpool School of Tropical MedicineLiverpoolUK
- CIBIO‐InBIO, Centro de Investigação em Biodiversidade e Recursos GenéticosCMUP, Centro de Matemática da Universidade do PortoPortoPortugal
| | - Jessica G. King
- School of Biological Sciences, Institute of Evolutionary BiologyUniversity of EdinburghEdinburghUK
| | - Ana Nunes
- Departamento de Física, Faculdade de CiênciasBioISI – Biosystems and Integrative Sciences Institute, Universidade de LisboaLisboaPortugal
| | - Nick Colegrave
- School of Biological Sciences, Institute of Evolutionary BiologyUniversity of EdinburghEdinburghUK
| | - Ary A. Hoffmann
- School of BioSciencesBio21 Institute, University of MelbourneMelbourneVic.Australia
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