An Agent-Based Model for Addressing the Impact of a Disaster on Access to Primary Care Services

Güçlü, Hasan; Kumar, Supriya; Galloway, David; Krauland, Mary G.; Sood, Rishi; Bocour, Angelica; Hershey, Tina Batra; Nostrand, Elizabeth Van; Potter, Margaret A.

doi:10.1017/dmp.2016.44

Cited by 7 publications

(9 citation statements)

References 30 publications

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“…Whereas MHCs provide an opportunity to provide access to primary care as sites reestablish their services postdisaster, planning within and coordination between primary care sites is important to ensure that populations impacted by a disaster continue to have access to health care. Through the development of an agent-based model to address the impact of Sandy on the Rockaways, 12 we found that the primary care access deficit increased after MHCs left the area after approximately 30 days. This suggests that coordination between governmental agencies and primary care sites regarding expected time period to reopen may help minimize primary care access deficits in a sustained manner.…”

Section: Resultsmentioning

confidence: 99%

Impact on Primary Care Access Post-Disaster: A Case Study From the Rockaway Peninsula

Sood

Bocour

Kumar

et al. 2016

Disaster med. public health prep.

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Section: Resultsmentioning

confidence: 99%

Impact on Primary Care Access Post-Disaster: A Case Study From the Rockaway Peninsula

Sood

Bocour

Kumar

et al. 2016

Disaster med. public health prep.

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“…FRED has previously been used to investigate a range of public health topics, including the benefits of paid sick leave and vaccination policies, positioning of health care facilities after natural disasters, and asthma and heat stroke risks during severe pollution events (Grefenstette & Schaper, 2017; Guclu et al, 2016; Liu et al, 2015). This study leverages FRED to investigate cigarette and e-cigarette use over time.…”

Section: Methodsmentioning

confidence: 99%

Integrating Social Dynamics Into Modeling Cigarette and E-Cigarette Use

et al. 2020

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Background. The use of electronic cigarettes (e-cigarette) offers potential to facilitate cigarette smoking cessation, yet potentially increases risk of cigarette smoking initiation. This relationship has been primarily modeled in mathematical ways that often do not represent real-world complexities, which could inform decisions regarding local prevention programs or policies. Aims. To develop a model of cigarette and e-cigarette use that combines current research on tobacco use and incorporates real-world geographic and demographic data. Method. We used a platform for developing agent-based models with demographic information representative of the population in Pennsylvania. We developed three models of cigarette and e-cigarette use. The primary outcome for each was the total number of users for cigarette, e-cigarette, and total nicotine. The first model applied current cigarette and e-cigarette data, the second tested the effect of implementing a program of e-cigarette education and policies, and the third considered a social contagion factor, where local schools functioned as a transmission vector. Results. The baseline and social contagion models found an overall decline in cigarette use but an increase in e-cigarette and total nicotine use. The education/policies model had declines in all categories. Sensitivity analysis suggested the importance of nuanced e-cigarette/cigarette interactions when modeling tobacco use. Discussion. Public health campaigns that focus on reducing youth e-cigarette usage can have a large effect. Social contagion should be strongly considered when studying e-cigarette spread. Conclusion. Targeted public health campaigns focused on reducing school prevalence of e-cigarette use may be particularly valuable.

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“…These examples illustrate the wide applicability of agent-based modeling to public health problems, from infectious disease to violence. Scholars have also developed ABMs to inform the provision of health care services, including access to primary care services after a disaster (50), care coordination among patients with serious mental health problems (55), and participation in community-based oral health programs (78). Together, this body of work illustrates the ability of agent-based modeling to test competing theories and evaluate interventions in the presence of complex nonlinear influences.…”

Section: Applications Of Abms In Public Healthmentioning

confidence: 99%

Agent-Based Modeling in Public Health: Current Applications and Future Directions

Tracy

Cerdá

Keyes

2024

Annual Review of Public Health

240

185

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Agent-based modeling is a computational approach in which agents with a specified set of characteristics interact with each other and with their environment according to predefined rules. We review key areas in public health where agent-based modeling has been adopted, including both communicable and noncommunicable disease, health behaviors, and social epidemiology. We also describe the main strengths and limitations of this approach for questions with public health relevance. Finally, we describe both methodologic and substantive future directions that we believe will enhance the value of agent-based modeling for public health. In particular, advances in model validation, comparisons with other causal modeling procedures, and the expansion of the models to consider comorbidity and joint influences more systematically will improve the utility of this approach to inform public health research, practice, and policy.

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An Agent-Based Model for Addressing the Impact of a Disaster on Access to Primary Care Services

Abstract: An agent-based model may be a useful tool to have in place so that policy makers can conduct scenario-based analyses to plan interventions optimally in the event of a disaster. (Disaster Med Public Health Preparedness. 2016;10:386-393).

Cited by 7 publications

References 30 publications

Impact on Primary Care Access Post-Disaster: A Case Study From the Rockaway Peninsula

Impact on Primary Care Access Post-Disaster: A Case Study From the Rockaway Peninsula

Integrating Social Dynamics Into Modeling Cigarette and E-Cigarette Use

Agent-Based Modeling in Public Health: Current Applications and Future Directions

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