Isolated Coronavirus Policies and Models Create Perverse Incentives for Disaster Preparedness

Policies and models concerning the novel coronavirus disease (COVID-19) that operate on the assumption that preparedness and response will occur under typical circumstances and not concurrent with other disasters—such as hurricanes or wildfires—may create perverse incentives to plan and prepare for only one disaster at a time. Planning and preparing for a single disaster is a problem because populations often experience mass migration in response to disasters, and planned disaster responses typically incorporate congregate shelter. Both long-distance migration and clustering in temporary shelters undermine social distancing as a mitigation strategy.

Across the United States, current COVID-19 policies and models of disease trajectories do not take into account the risk of multiple, concurrent disasters, and therefore may incentivize broad under-preparedness to address SARS-CoV-2 transmission during extenuating circumstances as we move into hurricane, tornado, flood, and wildfire season. In the case of recent, unprecedented flooding in Midland, MI, emergency response measures utilized traditional flood evacuation protocols associated with a high risk of COVID-19 spread. This under-preparedness risked increased COVID-19 spread, morbidity, and mortality.

Racial or ethnic minority groups, as a result of centuries of strategic political and economic oppression, are at highest risk of contracting and experiencing adverse health outcomes and mortality from COVID-19,[1][2] and adverse consequences, morbidity, and mortality from natural disasters.[3][4] In this persistent pandemic state, the United States cannot afford to promote siloed emergency planning and preparedness across various types of public health emergencies without further exacerbating health disparities. As such, we urge policymakers to establish disaster plans that explicitly incorporate the context of our current global pandemic.

COVID-19 and Disasters

Most US states, and many countries around the world, are gradually re-opening after several months of government-mandated social distancing designed to reduce the spread and mortality due to COVID-19. Implicit in the reopening plans is the idea that social distancing can be re-established if the epidemic spikes owing to the increased number of person-to-person contacts. That is, as a society, we assume that most travel and most gatherings are voluntary and can be stopped as needed.[5]

However, many seasonal natural disasters will soon be starting in the United States. Hurricanes in the southeastern states and eastern seaboard, flooding in the Midwest, and wildfires in the western states all peak in the summer and fall. In response to severe natural disasters, many people are forced to travel and/or seek large, long-term cohousing situations. Such events remove the fail-safe option of a return to social distancing from the COVID-19 reopening plans, as it is neither practical nor ethical to mandate that people remain in an area impacted by a natural disaster.

Several types of non-optional movements are particularly concerning in light of the available information about SARS-CoV-2 epidemiology. First, people in the impacted area may need to evacuate prior to the disaster occurring. Many will need to travel long distances to find alternate housing, including to other states. Genetic data have shown that the largest US SARS-CoV-2 outbreak was seeded by a small number of initial introductions, indicating that disaster-related, long-distance movements could result in similar outbreaks over large geographical areas.[6] Following the disaster, both professional and volunteer responders may converge on the impacted area. These movements carry the risk of introducing the virus in the impacted area, with the added concern that medical services in the location are likely to be disrupted.

In addition to long-distance movement, natural disasters can cause disruption to housing situations. Displaced people are often temporarily housed in large structures. Such housing situations, similar to those observed to result in high infection rates in prisons and long-term care facilities, present an extremely high risk for the spread of a respiratory virus such as SARS-CoV-2.[7][8] Finally, people who are able to remain in their homes may experience disruption in essential services and be forced to seek necessities such as food and water at centralized, crowded locations. While less threatening than group housing, such distribution centers also carry the risk of extensive viral spread. Taken together, these observations about the intersection of SARS-CoV-2 epidemiology and traditional disaster response show that advanced planning is necessary to mitigate the spread of the virus during the disaster season.

Current Policies

We conducted a search of all enacted state COVID-19 policies and developed plans as of May 2020, and all non-ensemble coronavirus models currently utilized by the Centers for Disease Control and Prevention (CDC) as of June 1, 2020 for pandemic planning purposes in jurisdictions across the United States, in order to determine the extent to which policies, plans, and models account for added disruption and movement of persons during disasters that would exacerbate COVID-19 risks.

Current state legislation and plans addressing COVID-19 prevention and response across the United States do not take into account the risk of other natural disasters or epidemics. No states have currently established COVID-19 legislation or plans that explicitly reference or recognize the exacerbated risk of COVID-19 during other disaster scenarios, and subsequently no legislation or plans seek to offer planning or solutions for COVID-19 mitigation during disaster scenarios. As shown in Table 1, only seven states established COVID-19 legislation that references other disasters, broadly. These policies do not reference or recognize risk or offer planning or solutions, but do expand some resources “during disasters” or emergencies. Two states, Arkansas and Hawaii, established legislation allowing virtual policy meetings during disasters in order to reduce crowding. Although specific risks of concurrent disasters are not recognized, these pieces of legislation provide the most direct protection under a broad array of disaster scenarios.

Table 1: State Policies and Plans and Disaster Risk

Policy Type (Plan/ Legislation)Policy NameStateIncorporates Other Disasters?Details Pertaining to Other Disasters
LegislationHB 1082ArkansasIndirectlyAllows for electronic public meetings for disaster preparedness to reduce crowding
LegislationHI SR 197HawaiiIndirectlyAllows legislature to hold virtual meetings during disasters
LegislationKS S 142KansasIndirectlyAllows school waiver during disasters
LegislationMN S 2225MinnesotaIndirectlyIncreases agricultural relief fund during disasters
LegislationNJ S 2353New JerseyIndirectlySeeks to narrow job loss definitions during times of emergency/disaster
LegislationHB 3411South CarolinaIndirectlyDisaster trust fund expansion
LegislationHB 3UtahIndirectlyDisaster appropriations fund expansion
We conducted a search of enacted state coronavirus legislation using the National Conference of State Legislatures coronavirus legislation database, in addition to a search of state coronavirus reopening plans using the Ballotpedia database of state reopening plans. Content analysis was conducted to review the inclusion of other disasters in any capacity in the legislation and plans. No state reopening plans included provisions related to other disasters. Seven states had enacted legislation that referenced ‘disasters’ broadly as opposed to solely the coronavirus.

Further, the current and most widely cited models projecting the trajectory of SARS-CoV-2 spread (and COVID-19 cases and mortality) do not take into account the risk of other extenuating scenarios, such as concurrent disasters, that would change projected behavior and therefore the spread of SARS-CoV-2. As shown in Table 2, all of the CDC models incorporate either data or assumptions about the population’s movement, distances traveled, and contact rates, including adjustments to these parameters in response to government policy. Models incorporate policy impacts either by using parameters that can be altered by the modelers in response to changing policy, or by estimating parameters from data on populations experiencing government-mandated social distancing.  Four of the models intentionally explore parameter spaces with transmission or movement rates higher than baseline pre-COVID rates, as might be expected during a natural disaster, although the models do not specifically attempt to model disaster situations.

Table 2: CDC COVID-19 Epidemiological Models and Disaster Risk

Model NameScale of PredictionIncorporates Disaster?Incorporates Current Policy Measures?aExplores Elevation of Contact Rate Above Baseline?b
Institute of Health Metrics and EvaluationState LevelNoParameter
manipulation
No
University of Texas, AustinState and Major US CitiesNoParameter
estimation
No
University of ArizonaState LevelNoParameter
estimation
No
University of Geneva/Swiss Data Science CenterState LevelNoParameter
estimation
No
Auquan Data ScienceState LevelNoParameter
manipulation
Allows manual increase of contact rate parameter
Columbia UniversityNationalNoParameter
manipulation
Includes one-time elevation when political measures loosen
COVID Act NowNationalNoParameter
manipulation
No
Johns Hopkins UniversityState LevelNoParameter
manipulation
No
Massachusetts Institute of TechnologyState LevelNoParameter
manipulation
No
Northeastern UniversityState LevelNoParameter
manipulation
No
University of California, Los AngelesState Level, California Counties, Los Angeles Metropolitan Area MunicipalitiesNoParameter
estimation
No
Youyang GuState Level, Subset of CountiesNoParameter
manipulation
Includes one-time elevation when political measures loosen
Los Alamos National LabsState LevelNoParameter
manipulation
Models a stochastic increase in growth rate once per month, and a decrease four times per month
Imperial College, LondonNationalNoParameter
estimation
No
Iowa State UniversityNationalNoParameter
manipulation
No
Georgia Institute of Technology, College of ComputingState LevelNoParameter
manipulation
No
We retrieved and reviewed all non-ensemble epidemiological models cited by the Centers for Disease Control and Prevention as of June 1, 2020 in their ongoing monitoring of coronavirus disease in the United States. We use the models listed on their “COVID-19 Forecasts: Cumulative Deaths” website.[9]
aSome models allow modelers to directly manipulate parameters that incorporate the effects of social distancing or other government interventions into their mortality projects. These models, which we put in the ‘parameter manipulation’ category, could be used to project the impacts of a natural disaster before it occurs. The models in the ‘parameter estimation’ category incorporate the effects of government interventions by estimating parameters from data gathered from populations under those interventions. These models will respond to disasters as data is collected in the days or weeks following the disaster.
bModels that already incorporate the possibility of contacts increasing above baseline levels may provide insight into the potential impacts of disasters on COVID mortality

Midland, Michigan – Flooding and Coronavirus

Beginning May 18, 2020, heavy rain and human error contributed to several dams being breached in Midland County, Michigan.[10] The floodwaters rose 38 feet, displacing 11,000 people in the city of Midland and surrounding areas. Evacuees could find their own housing or find shelter in one of five locations: two family centers and three local high schools, all opened on May 19. Among the evacuated buildings was a senior living facility. On May 21, residents who were able began returning to their homes. However, flood waters remained high for some weeks following the crest of the flood.[10] Flood zones in both Midland City and County—similar to many municipalities across the United States—correspond to lower-income neighborhoods,[11][12] exacerbating risks for already disadvantaged groups.

While estimates are unavailable for the number of people at Midland’s five emergency shelters, people living in crowded conditions for extended periods of time are highly susceptible to transmission of SARS-CoV-2. The majority of case studies of indoor SARS-CoV-2 spread come from hospitals. In these settings, even though airflow is carefully managed to minimize viral spread, the virus is sometimes detected in the airspace surrounding COVID-19 patients.[13][14][15] Outside of carefully controlled hospital environments, SARS-CoV-2 can spread quickly when many people occupy single buildings, particularly those with improperly managed HVAC-style air conditioning systems,[16] and in smaller, enclosed rooms.[14]

Policy Recommendations

Isolated COVID-19 policies and models may create perverse incentives to prepare and plan for only one disaster at a time. This design undermines the reality that SARS-CoV-2 is a new, constant threat that will persist alongside other long recognized threats, such as hurricane season, in addition to new threats in an evolving climate. While failing to address the reality of concurrent disasters will adversely affect the population as a whole, siloed emergency planning will specifically compound risks for low-income and racial or ethnic minority group members who already face the greatest threats from both COVID-19 and natural disasters, in isolation.

We urge policymakers at the federal, state, and local levels to establish disaster plans that explicitly incorporate the context of our current global pandemic and develop COVID-19 policies and models that take into account the elevated risks of concurrent disasters.  Additionally, states and municipalities will need to work together in their pandemic planning adaptation for disaster preparedness. As persons are often displaced during disasters, mass migration will hinder contact tracing if it is limited to single jurisdictions.

As discussed, emergency group housing—the default for evacuees in natural disasters-is particularly dangerous for SARS-CoV-2 spread. When group housing cannot be avoided, planners should mitigate spread by making cloth masks available in emergency housing.[17][18] While emergency housing is by definition ad-hoc, federal, state, and local planners should take into account best practices to avoid viral transmission to the greatest extent possible.[19][20]

Intergovernmental coordination of COVID-19 containment and mitigation is necessary for incorporating effective disaster planning and preparedness in the context of the pandemic, and for preventing exacerbated health disparities in high risk groups.

References

[1] Haggins A, Geronimus A. Racial disparities in the time of COVID-19. IHPI News. 2020. Available from: https://ihpi.umich.edu/news/racial-disparities-time-covid-19. Accessed July 3, 2020.
[2] Abuelgasim E, Saw LJ, Shirke M, Zeinah M, Harky A. COVID-19: Unique public health issues facing Black, Asian and minority ethnic communities. Curr Probl Cardiol. 2020;45(8):100621. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7207142/. Accessed July 3, 2020.
[3] Sovacool BK, Tan-Mullins M, Abrahamse W. Bloated bodies and broken bricks: Power, ecology, and inequality in the political economy of natural disaster recovery. World Dev. 2018;110:243-55. https://www.sciencedirect.com/science/article/pii/S0305750X18301761. Accessed July 3, 2020.
[4] Substance Abuse and Mental Health Service Administration. Greater Impact: How Disasters Affect People of Low Socioeconomic Status. 2017. https://www.samhsa.gov/sites/default/files/dtac/srb-low-ses_2.pdf. Accessed July 3, 2020.
[5] Wilder-Smith A, Freedman DO. Isolation, quarantine, social distancing and community containment: Pivotal role for old-style public health measures in the novel coronavirus (2019-nCoV) outbreak. J Travel Med. 2020;27(2):1-4.
[6] Gonzalez-Reiche AS, Hernandez MM, Sullivan M, Ciferri B, Alshammary H, Obla A, et al. Introductions and early spread of SARS-CoV-2 in the New York City area Ana. medRxiv. 2020;April:1-22. https://www.medrxiv.org/content/10.1101/2020.04.08.20056929v2. Accessed July 3, 2020.
[7] Wallace M, Hagan L, Curran KG, Williams SP, Handanagic S, Bjork A, et al. COVID-19 in correctional and detention facilities – United States, February–April 2020. Morb Mortal Wkly Rep. 2020;69(19):19-22.
[8] McMichael TM, Currie DW, Clark S, Pogosjans S, Kay M, Schwartz NG, et al. Epidemiology of Covid-19 in a long-term care facility in King County, Washington. N Engl J Med. 2020;1-7.
[9] Centers for Disease Control and Prevention. COVID-19 Forecasts: Cumulative Deaths. Mathematical Modeling. 2020. Available from: https://www.cdc.gov/coronavirus/2019-ncov/covid-data/forecasting-us.html. Accessed June 1, 2020.
[10] Midland Michigan. Midland, MI Official Website: Civic Alerts. News Flash. 2020 https://cityofmidlandmi.gov/CivicAlerts.aspx?sort=date. Accessed July 3, 2020.
[11] DataUSA. Midland, MI. Profile. 2020. Available from: https://datausa.io/profile/geo/midland-mi. Accessed July 4, 2020.
[12] City of Midland. City of Midland Flood Map. 2008. Available from: http://www2.midland-mi.org/custom_maps/floodmap.htm. Accessed July 4, 2020.
[13] Setti L, Passarini F, De Gennaro G, Barbieri P, Perrone MG, Borelli M, et al. Airborne transmission route of covid-19: Why 2 meters/6 feet of inter-personal distance could not be enough. Int J Environ Res Public Health. 2020;17(8).
[14] Liu Y, Ning Z, Chen Y, Guo M, Liu Y, Gali NK, et al. Aerodynamic analysis of SARS-CoV-2 in two Wuhan hospitals. Nature. 2020;582.
[15] Chia PY, Coleman KK, Tan YK, Ong SWX, Gum M, Lau SK, et al. Detection of air and surface contamination by SARS-CoV-2 in hospital rooms of infected patients. Nat Commun. 2020;11(1).
[16] Correia G, Rodrigues L, Gameiro da Silva M, Gonçalves T. Airborne route and bad use of ventilation systems as non-negligible factors in SARS-CoV-2 transmission. Med Hypotheses. 2020;141:109781. https://doi.org/10.1016/j.mehy.2020.109781. Accessed July 4, 2020.
[17] Rodriguez-Palacios A, Cominelli F, Basson AR, Pizarro TT, Ilic S. Textile masks and surface covers—A spray simulation method and a “universal droplet reduction model” against respiratory pandemics. Front Med. 2020;7:1-11.
[18] Clase CM, Bchir MB, Fu EL, Joseph M, Beale RCL, Dolovich MB, et al. Cloth masks may prevent transmission of COVID-19: An evidence-based, risk-based approach. Ann Intern Med. 2020;1(10):1-4.
[19] Allen JG, Marr LC. Recognizing and controlling airborne transmission of SARS-CoV-2 in indoor environments. Indoor Air. 2020;30(4):557-558.
[20] Dietz L, Horve PF, Coil DA, Fretz M, Eisen JA, Wymelenberg K Van Den. 2019 Novel Coronavirus (COVID-19) pandemic: Built environment considerations to reduce transmission. MSystems. 2020;5(2):1-13.


Citation:
Willison C, Holmes I. Isolated Coronavirus Policies and Models Create Perverse Incentives for Disaster Preparedness. Milbank Quarterly Opinion. July 30, 2020. https://doi.org/10.1599/mqop.2020.0730


About the Authors

Charley Willison, PhD, MPH, MA, is a National Institutes of Mental Health Postdoctoral Fellow at the Harvard University Department of Health Care Policy and the Health Equity Research Lab. Charley completed her PhD at the University of Michigan School of Public Health. She studies the effects of urban politics and intergovernmental relations on public health political decision-making and public health policy outcomes. Substantively, her work focuses on health policies that are designed and or delivered at the local level including: homelessness, behavioral health policies, and disaster responses.

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Iris Holmes, PhD, is a postdoctoral fellow at the Cornell Institute of Host-Microbe Interactions and Disease. She received her PhD from the University of Michigan Department of Ecology and Evolutionary Biology in April 2020. She is broadly interested in the factors that determine microbial transmission within and between host species, with a particular focus on the impact of biological community context on the ecological and evolutionary trajectories of pathogens and parasites.

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