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Remote Laboratory Management: Respiratory Virus Diagnostics
Published on: April 6, 2019
Operational response simulation tool for epidemics within refugee and IDP settlements: A scenario-based case study of
Joseph Aylett-Bullock1,2, Carolina Cuesta-Lazaro2, Arnau Quera-Bofarull2
1United Nations Global Pulse, New York, New York, United States of America.
Insights
Agent-based modeling shows self-isolation for mild COVID-19 cases and indoor mask-wearing effectively reduce disease spread in refugee settlements. Reopening learning centers is feasible with layered mitigation strategies.
Area of Science:
- Epidemiology
- Computational modeling
- Public health
Background:
- Infectious disease outbreaks like COVID-19 disproportionately affect vulnerable populations, including those in refugee and internally displaced person (IDP) settlements.
- High population density and limited infrastructure in settlements increase susceptibility to rapid disease transmission.
Purpose of the Study:
- To develop and apply an agent-based model simulating disease spread in refugee settlements.
- To evaluate the effectiveness of various non-pharmaceutical intervention (NPI) strategies in mitigating infectious disease transmission.
Main Methods:
- Utilized an agent-based modeling approach based on the open-source June framework.
- Incorporated real-world data on geography, demographics, comorbidities, and infrastructure for the Cox's Bazar settlement, aiming for generalizability.
Main Results:
- Self-isolating symptomatic individuals at home, rather than in dedicated centers, does not increase secondary infections and allows centers for severe cases.
- Indoor mask-wearing effectively dampens viral spread, even with low compliance and efficacy.
- Reopening learning centers is viable with mask mandates, reduced attendance, and improved ventilation, nearly eliminating increased infection risk.
Conclusions:
- NPIs can be tailored to settlement contexts, optimizing resource allocation and protecting vulnerable populations.
- Modeling provides crucial data for informing public health policies and planning in informal settlements during outbreaks.
- Further research in similar settings is recommended to refine strategies and safeguard at-risk communities.
Abstract:
The spread of infectious diseases such as COVID-19 presents many challenges to healthcare systems and infrastructures across the world, exacerbating inequalities and leaving the world's most vulnerable populations most affected. Given their density and available infrastructure, refugee and internally displaced person (IDP) settlements can be particularly susceptible to disease spread. In this paper we present an agent-based modeling approach to simulating the spread of disease in refugee and IDP settlements under various non-pharmaceutical intervention strategies. The model, based on the June open-source framework, is informed by data on geography, demographics, comorbidities, physical infrastructure and other parameters obtained from real-world observations and previous literature. The development and testing of this approach focuses on the Cox's Bazar refugee settlement in Bangladesh, although our model is designed to be generalizable to other informal settings. Our findings suggest the encouraging self-isolation at home of mild to severe symptomatic patients, as opposed to the isolation of all positive cases in purpose-built isolation and treatment centers, does not increase the risk of secondary infection meaning the centers can be used to provide hospital support to the most intense cases of COVID-19. Secondly we find that mask wearing in all indoor communal areas can be effective at dampening viral spread, even with low mask efficacy and compliance rates. Finally, we model the effects of reopening learning centers in the settlement under various mitigation strategies. For example, a combination of mask wearing in the classroom, halving attendance regularity to enable physical distancing, and better ventilation can almost completely mitigate the increased risk of infection which keeping the learning centers open may cause. These modeling efforts are being incorporated into decision making processes to inform future planning, and further exercises should be carried out in similar geographies to help protect those most vulnerable.
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