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      Disaster displacement and zoonotic disease dynamics: The impact of structural and chronic drivers in Sindh, Pakistan

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          Abstract

          Projected increases in human and animal displacement driven by climate change, disasters and related environmental degradation will have significant implications to global health. Pathways for infectious disease transmission including zoonoses, diseases transmitted between animals and humans, are complex and non-linear. While forced migration is considered an important driver for the spread of zoonoses, actual disease dynamics remain under researched. This paper presents the findings of a case study investigating how disaster displacement affected zoonotic disease transmission risk following the 2010 ‘superfloods’ in Sindh province, Pakistan. We interviewed 30 key informants and 17 household members across 6 rural communities between March and November 2019, supported by observational studies and a review of secondary data. Results were analysed using the ecosocial theoretical framework. Buffalo, cattle and goats were often the only moveable asset, therefore livestock was an important consideration in determining displacement modality and destination location, and crowded locations were avoided to protect human and animal health. Meanwhile however, livestock was rarely included in the humanitarian response, resulting in communities and households fragmenting according to the availability of livestock provisions. We found that rather than a driver for disease, displacement acted as a process affecting community, household and individual zoonotic disease risk dynamics, based on available resources and social networks before, during and after displacement, rooted in the historical, political and socio-economic context. We conclude that in rural Sindh, disaster displaced populations’ risk of zoonoses is the result of changes in dynamics rooted in pre-existing structural and chronic inequalities, making people more or less vulnerable to disease through multiple interlinked pathways. Our findings have implications for policy makers and humanitarian responders assisting displaced populations dependent on livestock, with a call to integrate livestock support in humanitarian policies and responses for health, survival and recovery.

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          Most cited references80

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          Are We There Yet? Data Saturation in Qualitative Research

          Failure to reach data saturation has an impact on the quality of the research conducted and hampers content validity. The aim of a study should include what determines when data saturation is achieved, for a small study will reach saturation more rapidly than a larger study. Data saturation is reached when there is enough information to replicate the study when the ability to obtain additional new information has been attained, and when further coding is no longer feasible. The following article critiques two qualitative studies for data saturation: Wolcott (2004) and Landau and Drori (2008). Failure to reach data saturation has a negative impact on the validity on one’s research. The intended audience is novice student researchers.
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            Thematic networks: an analytic tool for qualitative research

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              A simple method to assess and report thematic saturation in qualitative research

              Data saturation is the most commonly employed concept for estimating sample sizes in qualitative research. Over the past 20 years, scholars using both empirical research and mathematical/statistical models have made significant contributions to the question: How many qualitative interviews are enough? This body of work has advanced the evidence base for sample size estimation in qualitative inquiry during the design phase of a study, prior to data collection, but it does not provide qualitative researchers with a simple and reliable way to determine the adequacy of sample sizes during and/or after data collection. Using the principle of saturation as a foundation, we describe and validate a simple-to-apply method for assessing and reporting on saturation in the context of inductive thematic analyses. Following a review of the empirical research on data saturation and sample size estimation in qualitative research, we propose an alternative way to evaluate saturation that overcomes the shortcomings and challenges associated with existing methods identified in our review. Our approach includes three primary elements in its calculation and assessment: Base Size, Run Length, and New Information Threshold. We additionally propose a more flexible approach to reporting saturation. To validate our method, we use a bootstrapping technique on three existing thematically coded qualitative datasets generated from in-depth interviews. Results from this analysis indicate the method we propose to assess and report on saturation is feasible and congruent with findings from earlier studies.

                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: InvestigationRole: Project administrationRole: ResourcesRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: MethodologyRole: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLOS Glob Public Health
                PLOS Glob Public Health
                plos
                PLOS Global Public Health
                Public Library of Science (San Francisco, CA USA )
                2767-3375
                8 December 2021
                2021
                : 1
                : 12
                : e0000068
                Affiliations
                [1 ] Disease Dynamics Unit, Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
                [2 ] Department of Economics, University of Sindh, Sindh, Pakistan
                [3 ] Department of Anthropology, University College London, London, United Kingdom
                Mzuzu University, MALAWI
                Author notes

                The authors declare no competing financial, personal, or professional interests that could be construed to have influenced the work.

                Author information
                https://orcid.org/0000-0002-6011-2392
                https://orcid.org/0000-0003-3256-0099
                https://orcid.org/0000-0003-3836-6078
                https://orcid.org/0000-0002-0258-3188
                Article
                PGPH-D-21-00107
                10.1371/journal.pgph.0000068
                10021430
                36962103
                ab1cb069-d2ca-4a8f-a8fb-72211035bc44
                © 2021 Braam et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 7 June 2021
                : 15 November 2021
                Page count
                Figures: 1, Tables: 0, Pages: 18
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100005370, Gates Cambridge Trust;
                Award ID: OPP1144
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100008288, Alborada Trust;
                Award Recipient :
                DB is funded by the Gates-Cambridge Trust (Bill & Melinda Gates Foundation [OPP1144]). JW is supported by The Alborada Trust. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Agriculture
                Animal Management
                Livestock
                Biology and Life Sciences
                Veterinary Science
                Veterinary Diseases
                Medicine and Health Sciences
                Epidemiology
                Medical Risk Factors
                Earth Sciences
                Hydrology
                Flooding
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Zoonoses
                Biology and Life Sciences
                Veterinary Science
                Veterinary Medicine
                Livestock Care
                Medicine and Health Sciences
                Health Care
                Socioeconomic Aspects of Health
                Medicine and Health Sciences
                Public and Occupational Health
                Socioeconomic Aspects of Health
                People and Places
                Geographical Locations
                Asia
                Pakistan
                Custom metadata
                All data generated or analysed during this study are included in this published article.

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