The Case for Controls: Identifying outbreak risk factors through case-control comparisons
Fuente:
arXiv
Guardado en:
| Autores principales: | , , , , , , , , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2023
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866911035503411200 |
|---|---|
| author | Fefferman, Nina H. Blum, Michael J. Bourouiba, Lydia Gibson, Nathaniel L. He, Qiang Miller, Debra L. Papes, Monica Pasquale, Dana K. Verheyen, Connor Ryan, Sadie J. |
| author_facet | Fefferman, Nina H. Blum, Michael J. Bourouiba, Lydia Gibson, Nathaniel L. He, Qiang Miller, Debra L. Papes, Monica Pasquale, Dana K. Verheyen, Connor Ryan, Sadie J. |
| contents | Investigations of infectious disease outbreaks often focus on identifying place- and context-dependent factors responsible for emergence and spread, resulting in phenomenological narratives ill-suited to developing generalizable predictive and preventive measures. We contend that case-control hypothesis testing is a more powerful framework for epidemiological investigation. The approach, widely used in medical research, involves identifying counterfactuals, with case-control comparisons drawn to test hypotheses about the conditions that manifest outbreaks. Here we outline the merits of applying a case-control framework as epidemiological study design. We first describe a framework for iterative multidisciplinary interrogation to discover minimally sufficient sets of factors that can lead to disease outbreaks. We then lay out how case-control comparisons can respectively center on pathogen(s), factor(s), or landscape(s) with vignettes focusing on pathogen transmission. Finally, we consider how adopting case-control approaches can promote evidence-based decision making for responding to and preventing outbreaks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2311_02226 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | The Case for Controls: Identifying outbreak risk factors through case-control comparisons Fefferman, Nina H. Blum, Michael J. Bourouiba, Lydia Gibson, Nathaniel L. He, Qiang Miller, Debra L. Papes, Monica Pasquale, Dana K. Verheyen, Connor Ryan, Sadie J. Populations and Evolution Investigations of infectious disease outbreaks often focus on identifying place- and context-dependent factors responsible for emergence and spread, resulting in phenomenological narratives ill-suited to developing generalizable predictive and preventive measures. We contend that case-control hypothesis testing is a more powerful framework for epidemiological investigation. The approach, widely used in medical research, involves identifying counterfactuals, with case-control comparisons drawn to test hypotheses about the conditions that manifest outbreaks. Here we outline the merits of applying a case-control framework as epidemiological study design. We first describe a framework for iterative multidisciplinary interrogation to discover minimally sufficient sets of factors that can lead to disease outbreaks. We then lay out how case-control comparisons can respectively center on pathogen(s), factor(s), or landscape(s) with vignettes focusing on pathogen transmission. Finally, we consider how adopting case-control approaches can promote evidence-based decision making for responding to and preventing outbreaks. |
| title | The Case for Controls: Identifying outbreak risk factors through case-control comparisons |
| topic | Populations and Evolution |
| url | https://arxiv.org/abs/2311.02226 |