Observations and conversations: how communities learn about infection risk can impact the success of non-pharmaceutical interventions against epidemics

Influence of Lived Experiences on Public Responses to Future Diseases via (De)Sensitization of Concern

OBJECTIVES

Public responses to a future novel disease might be influenced by a subset of individuals who are either sensitized or desensitized to concern-generating processes through their lived experiences during the coronavirus disease 2019 (COVID-19) pandemic. Such influences may be critical for shaping public health messaging during the next emerging threat.

METHODS

This study explored the potential outcomes of the influence of lived experiences by using a dynamic multiplex network model to simulate a COVID-19 outbreak in a population of 2000 individuals, connected by means of disease and communication layers. Then a new disease was introduced, and a subset of individuals (50% or 100% of hospitalized during the COVID-19 outbreak) was assumed to be either sensitized or desensitized to concern-generating processes relative to the general population, which alters their adoption of non-pharmaceutical interventions (social distancing).

RESULTS

Altered perceptions and behaviors from lived experiences with COVID-19 did not necessarily result in a strong mitigating effect for the novel outbreak. When public disease response is already strong or sensitization is assumed to be a robust effect, then a sensitized subset may enhance public mitigation of an outbreak through social distancing.

CONCLUSIONS

In preparing for future outbreaks, assuming an experienced and disease-aware public may compromise effective design of effective public health messaging and mitigative action.

Linking Immuno-Epidemiology Principles to Violence

Background

Societies have always struggled with violence, but recently there has been a push to understand violence as a public health issue. This idea has unified professionals in medicine, epidemiological, and psychology with a goal to end violence and heal those exposed to it. Recently, analogies have been made between community-level infectious disease epidemiology and how violence spreads within a community. Experts in public health and medicine suggest an epidemiological framework could be used to study violence.

Methods

Building upon results from community organizations which implement public health-like techniques to stop violence spread, we look to formalize the analogies between violence and infectious diseases. Then expanding on these ideas and using mathematical epidemiological principals, we formulate a susceptible-exposed-infected model to capture violence spread. Further, we ran example numerical simulations to show how a mathematical model can provide insight on prevention strategies.

Results

The preliminary simulations show negative effects of violence exposure have a greater impact than positive effects of preventative measures. For example, our simulation shows that when the impact of violence exposure is reduced by half, the amount of violence in a community drastically decreases in the long-term; but to reach this same outcome through an increase in the amount of after exposure support, it must be approximately fivefold. Further, we note that our simulations qualitatively agree with empirical studies.

Conclusions

Having a mathematical model can give insights on the effectiveness of different strategies for violence prevention. Based on our example simulations, the most effective use of community funding is investing in protective factors, instead of support after violence exposure, but of course these results do not stand in isolation and will need to be contextualized with the rest of the research in the field.

How reported outbreak data can shape individual behavior in a social world

Agencies reporting on disease outbreaks face many choices about what to report and the scale of its dissemination. Reporting impacts an epidemic by influencing individual decisions directly, and the social network in which they are made. We simulated a dynamic multiplex network model—with coupled infection and communication layers—to examine behavioral impacts from the nature and scale of epidemiological information reporting. We explored how adherence to protective behaviors (social distancing) can be facilitated through epidemiological reporting, social construction of perceived risk, and local monitoring of direct connections, but eroded via social reassurance. We varied reported information (total active cases, daily new cases, hospitalizations, hospital capacity exceeded, or deaths) at one of two scales (population level or community level). Total active and new case reporting at the population level were the most effective approaches, relative to the other reporting approaches. Case reporting, which synergizes with test-trace-and-isolate and vaccination policies, should remain a priority throughout an epidemic.

Association of Trends in Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Seroprevalence and State-Issued Nonpharmaceutical Interventions: United States, 1 August 2020 to 30 March 2021

BACKGROUND

We assess if state-issued nonpharmaceutical interventions (NPIs) are associated with reduced rates of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection as measured through anti-nucleocapsid (anti-N) seroprevalence, a proxy for cumulative prior infection that distinguishes seropositivity from vaccination.

METHODS

Monthly anti-N seroprevalence during 1 August 2020 to 30 March 2021 was estimated using a nationwide blood donor serosurvey. Using multivariable logistic regression models, we measured the association of seropositivity and state-issued, county-specific NPIs for mask mandates, gathering bans, and bar closures.

RESULTS

Compared with individuals living in a county with all three NPIs in place, the odds of having anti-N antibodies were 2.2 (95% confidence interval [CI]: 2.0-2.3) times higher for people living in a county that did not have any of the 3 NPIs, 1.6 (95% CI: 1.5-1.7) times higher for people living in a county that only had a mask mandate and gathering ban policy, and 1.4 (95% CI: 1.3-1.5) times higher for people living in a county that had only a mask mandate.

CONCLUSIONS

Consistent with studies assessing NPIs relative to COVID-19 incidence and mortality, the presence of NPIs were associated with lower SARS-CoV-2 seroprevalence indicating lower rates of cumulative infections. Multiple NPIs are likely more effective than single NPIs.