Rocky Mountain West COVID-19 Modeling: A descriptive assessment of the current public health needs during the COVID-19 pandemic to endemic transition

doi:10.21203/rs.3.rs-3246371/v1

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Rocky Mountain West COVID-19 Modeling: A descriptive assessment of the current public health needs during the COVID-19 pandemic to endemic transition

https://doi.org/10.21203/rs.3.rs-3246371/v1

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Background: Mathematical models of infectious diseases have played a key role in the response to the COVID-19 pandemic and many prior infectious disease outbreaks. Effective models require understanding decision-makers' needs. While much attention was placed on the needs of public health leaders in the early phase of the pandemic, by summer 2022, the way needs evolved was poorly documented. Moreover, needs in rural areas have never been well-understood. Getting a more complete and up-to-date description of these needs is key to designing modeling and data visualization tools that can aid in public health response.

Methods: We conducted semi-structured interviews with public health leaders representing state, local, and tribal health departments in the Rocky Mountain West in the summer of 2022 to understand their priorities, decision-making needs, and data resources over two years into the COVID-19 pandemic.

Results: Public health leaders from six organizations representing three states, local, regional, and tribal public health agencies in the Rocky Mountain West participated in our interviews. Responses to priorities and needs covered a broad range of topics. Priorities included having timely information on vaccines, anticipating COVID-19 demands on hospitals, understanding the potential impacts of emerging variants and communicating immunity concepts to the public. Decisions focused on making public health recommendations as opposed to mandates. Travel-related introductions of SARS-CoV-2 infections were not a present concern compared to earlier in the pandemic. Limited access to timely COVID-19 data and challenges tracking COVID-19 hospitalizations was a challenge mentioned by multiple interviewees.

Conclusions: Over two years since SARS-CoV-2 emerged, there is still an important role for modeling during epidemic and pandemic responses. There remain major gaps in data availability, particularly related to COVID-19 hospital demand, that make it challenging to utilize timely and granular data to inform and parameterize models.

COVID-19

SARS-CoV-2

surveillance

public health practice

pandemic

Previous epidemics and pandemics, such as SARS-CoV-1, the 2009 influenza pandemic, and the Zika pandemic, spurred academic-public health collaborations that were critical to understanding early characteristics of the pandemic pathogen and helped lay the groundwork for collaborations during COVID-19. During the COVID-19 pandemic, initiatives such as the COVID-19 Forecasts (1) and the COVID-19 Scenario Modeling Hub (2), have underscored the strength and utility of such partnerships, through which academics can provide additional technical and analytical support to public health agencies, and public health agencies can guide development of critical questions. They can also provide practical feedback and operational insight while utilizing the outputs from model projections and forecasts as part of their decision making. Large-scale initiatives, such as the COVID-19 Scenario Modeling Hub, focus on generating projections at a national level. However, many academic institutions have also partnered with local, state, and territorial health departments in COVID-19 modeling efforts to generate state, county or city-specific COVID-19 hospitalization projections (3–5). While many modeling efforts have aided decision-making, there are still gaps in understanding how infectious disease modeling can meet the current needs of public health agencies. There is a need to identify the priorities of local, state, and regional public health departments at this transitional stage of the COVID-19 pandemic, in order to ensure COVID-19 models evolve in response to decision-making needs.

The pandemic shed light on the long-standing gaps and underfunding of critical public health systems. These include issues with data transparency, accessibility, and timeliness (6). Early assessments also found little data reported on vulnerable populations, and these gaps in surveillance continue to exacerbate COVID-19 inequities (7, 8). However, many of these assessments were conducted during the two years of the pandemic (2020–2021). Examining whether these workforce and public health capability needs still exist is critical to understanding how to continue improving and supporting public health departments as the organizations transition from pandemic response and to prepare for future pandemics.

The Colorado School of Public Health COVID-19 Modeling Group provided projections of COVID-19 hospitalizations for Colorado during the pandemic (5) and recently expanded their focus to the Rocky Mountain West (RMW). The RMW (Colorado, Idaho, Montana, New Mexico, Utah and Wyoming, and ) is a diverse and geographically expansive region that includes rural and frontier locations connected by large urban centers and resort communities that attract international and domestic tourists.(9) This region often does not follow connectivity and infectious disease transmission patterns like those observed in more densely connected regions of the United States like the Northeast. To improve our modeling approaches for COVID-19 for the RMW region, and identify how outputs from our mathematical model, like COVID-19 hospitalization projections, could align with regional and state priorities and concerns related to the COVID-19 pandemic, we held informational interviews with representatives and officials from regional, state, and local (including non-government based) public health departments from the RMW region between June and August 2022.

Study Design and Recruitment Approach

We identified a sample of public health representatives in the RMW region and interviewed them from June to August 2022 about their current COVID-19 priorities, data, and decision-making needs. The intent was to hear the perspectives of public health leaders on the front lines of the COVID-19 public health response and use their insights to tailor SARS-CoV-2 mathematical modeling tools to current and emerging needs. For the purposes of this study, we defined the RMW region as Colorado (CO), Idaho (ID), Montana (MT), New Mexico (NM), Utah (UT) and Wyoming (WY).

Recruitment involved targeted recruitment and snowball sampling (10). We created an initial list of representatives with affiliations at tribal, local, and state health departments across the RMW region. The Principal Investigator (EJC) contacted each potential participant via e-mail. Follow-up occurred via e-mail and/or phone call. Those who expressed interest in participating were scheduled for an interview. If a participant was unable or unwilling to participate, we asked them to recommend other people to contact. We also asked those who we did interview to recommend other potential participants.

Structure of Interview

We conducted virtual, semi-structured, 30-minute interviews with each participant. If multiple people from the same organization agreed to participate, a single interview was scheduled with all participating individuals from the organization. At least three Colorado School of Public Health COVID-19 Modeling Team members participated in each interview, one serving as interviewer and two as note-takers. To promote candid responses, interviews were not recorded. At the start of each interview, our team provided a brief overview of current COVID-19 modeling efforts, including background on the interview's purpose, followed by four questions (Table 1). Interview questions were developed by the team to solicit open-ended responses concerning 1) COVID-19 related priorities for their region, 2) the types of decisions related to COVID-19 that their organization is currently making, and the types of decisions anticipate having to make in the future, 3) their concerns about imported infections and variants, and 4) the data sources they used to track SARS-CoV-2, including hospital demand.

Table 1

Interview Questions
Categories	Interview Questions
Current Priorities	What are some of the most important COVID-related questions for your state or region at this time?
Current and anticipated future decision making	As the pandemic (and the public's perception of it) changes, what kinds of decisions related to COVID-19 will you and your fellow state and regional leaders need to make in the near- and long-term?
Strategies for detecting travel-associated cases and emerging variants	How concerned are you about the introduction of SARS-CoV-2 infections or new variants into your state or region from travelers? Are there ways that your state or region currently tracks this?
Data Sources	How does your team track COVID-19 hospitalizations in your state or region? What other supplemental COVID-19 data or resources does your team use in addition to core reportable disease data?

Interviewee characteristics

Thirteen public health organizations in six states in the RMW region were identified and contacted. Eight of the 13 organizations responded. Of those eight, five completed interviews, one group declined to participate, one group responded that they would like to participate but we were unable to schedule an interview, and one group did not respond to the invitation. We subsequently identified five additional groups based on participant suggestions as part of our efforts to ensure representation across the region. Representatives from one of these organizations agreed to participate and completed an interview. Overall, six groups participated in the interviews representing public health agencies at the local (n = 1), state (n = 3), and regional/tribal (n = 2) levels. Despite repeated attempts and outreach to multiple groups, we were unable to recruit participants from three states.

Descriptive Analysis

A descriptive analysis of interviewee responses for each question was conducted. Interview notes were consolidated into a single document from the two independent note-takers following each interview. Responses were then paraphrased to identify common responses for each interview question across the six interviewed groups. Some topics emerged in response to multiple questions. For brevity, we group together such responses below.

Current COVID-19 priorities

Interviewees reported several COVID-19 related public health priorities for their states and/or regions that centered around four overlapping themes: 1) vaccination and immunity, 2) hospital capacity and burden on the health care system 3) impact of emerging variants, and 4) changing surveillance indicators.

Common priorities related to vaccination and immunity included identifying: “Who is up to date on their vaccines and how will this look in the future?” and understanding the current state of immunity in interviewees’ geographical areas. This included how to improve uptake of vaccine boosters and identifying where gaps in vaccination could lead to COVID-19 “hotspots.”

Most interviewed public health officials said understanding the impact of SARS-CoV-2 on the healthcare system was a key priority—particularly the risk of hospitals exceeding hospital capacity as was the case early in the pandemic. Important questions included: “When will we run into hospital capacity issues?” and “what will hospital demands be?” Interviewees noted knowing when hospital surges were likely was helpful for staffing adjustments, potentially changing licensing requirements, and advising health facilities to prepare.

Detecting variants and their future impact was another Summer 2022 priority. Several interviewees reported challenges monitoring variants, noting lags in the sequencing pipeline and a limited number of sequenced samples. Interviewees from less densely populated regions noted that new variants typically arrived later in their communities, allowing them to watch and learn from regions impacted earlier. One group highlighted concerns about the potential impacts of variants on healthcare demand, asking “how bad would a variant have to be to see an increase this fall?”

The last major priority was changing surveillance indicators, and the use and interpretation of surveillance data. Changes to reported cases were broadly recognized as due to increases in at-home testing and decreases in funded testing sites. Interviewees acknowledged that testing patterns varied regionally. Two interviewees raised the issue of “decoupling of cases and hospitalizations” – high testing rates and high vaccination coverage in these areas meant low hospitalizations but high reported cases. The resulting pattern led these two groups to monitor COVID-19 hospitalizations and cases independently. One public health official expressed a desire to be able to estimate the true burden of infections across counties.

Other priority areas mentioned included uncertainty about which mitigation strategies are still working, better guidance on ventilation and its impact on the return to work and school, concerns about acceptance of communicable disease control methods by policymakers, and timely data sharing with tribal health centers and tribes.

Current and anticipated COVID-19 decision-making

Common responses focused on three key areas for near- and long-term decisions in Summer 2022: 1) COVID-19 mandates vs. recommendations; 2) allocation of resources for surveillance and care, and 3) science communication, specifically for COVID-19 vaccines.

Most near- and long-term decisions focused on transitioning from implementing mandates to making recommendations. One interviewee said, “decisions at the local and state public health level were pretty limited.” Instead, many groups described being in “recommendation mode,” often following the Centers for Disease Control and Prevention (CDC) guidelines. Respondents commonly stated that mask mandates were not an option in the future. Instead, they emphasized recommendations about mask-wearing, and several reported adopting CDC masking recommendations. A public health leader described shifting messaging strategies to promote high-quality masks “to protect yourself” (prior messaging emphasized masks to prevent the spread of infections by the infected). School boards and guidance surrounding ventilation were also briefly mentioned.

Resource allocation decisions for surveillance and care were commonly mentioned. One interviewee highlighted their state paid for SARS-CoV-2 testing and “Omicron broke the bank.” Allocation of therapeutics to healthcare facilities across the region and recommendations for Paxlovid treatment were also mentioned. Public health officials also reported being asked to provide input on decisions about the strain on healthcare capacity and staffing, including when and whether crisis standards of care will be needed, and if additional healthcare staffing should be requested.

Science communication was commonly mentioned when asked about current and anticipated decisions. Responses on this topic highlighted challenges beyond decision-making and the need to improve science communication in the future. Challenges for decision-makers focused on communicating health risks from new variants to the public and challenges related to public disengagement. One interviewee stated it was hard to imagine people following recommendations unless there was concrete data. Others wanted educational materials describing “how variants are different from each other.” Multiple groups said communication toolkits on these topics were needed for public health leaders. Regarding public disengagement, one interviewee noted their region had been at a high CDC community level for several weeks; when a local paper reported on this, the public was surprised. Another respondent highlighted the particular challenge of tourists, as many people on vacation didn’t want to think about COVID-19 and engaged in risky behaviors.

Interviewees identified needing better tools to communicate about vaccines and emerging variants to the public, and highlighted challenges to effectively promoting vaccines and boosters. Several wanted better tools for discussing immunity and vaccine impacts. One public health official noted breakthrough SARS-CoV-2 infections in vaccinated individuals led some people to remain unvaccinated. Another highlighted needing guidance for discussing more complex concepts to the public, such as distinguishing between infection-acquired and vaccine-acquired immunity. Interviewees provided sample questions that they needed help answering. For example: “My child had COVID, why should I get them vaccinated?” or: “I just had Omicron, why should I get vaccinated?” One group noted the need for information on reformulated boosters to improve booster uptake, and another group wanted estimates of the potential impact of vaccines and boosters for young children.

Strategies for detecting travel-associated cases and emerging variants

Travel-associated cases were of little concern to most of the groups interviewed. They cited reasons like: “everyone is traveling,” “the cat’s out of the bag” and, in rural regions, “open space.” Little travel-specific tracking was mentioned. One group said they tracked mobility data early in the pandemic and found it helpful to see the connectivity of communities. Only one region with considerable tourism reported actively monitoring travel patterns: by tracking mobility and occupancy rates at hotels to anticipate testing demand surges. Even this group noted low concern about COVID spread from travelers and greater concern about identifying potential high-resource demand periods.

Interviewees reported more concern about the emergence of SARS-CoV-2 variants. Strategies for tracking variants varied across groups. Most reported relying on genomic surveillance, with sources varying across departments. For example, some organizations with limited testing relied on external organizations’ reporting of variants, whereas others reported using in-house sequencing as part of case detection for new SARS-CoV-2 variants. One group stated that their goal was to detect the first time a variant is detected in their state. Another group noted that their level of concern was dependent on whether a new variant was more severe.

Monitoring of COVID-19 hospitalizations and other data sources

When asked about how they track hospitalizations in their respective locations, interviewees varied in their sources, their use of data to identify hospital capacity surges, ongoing challenges to data accessibility and timeliness, and supplementation of hospital data with additional sources.

Interviewees reported tracking COVID-19 hospitalizations using internal state and local hospital reporting systems, federal hospital data resources, and public and private data sources. Some states and local health agencies used bespoke surveillance systems including hospitalization data extracted from case reports, a statewide COVID-19 hospital surveillance system, and a regional health information exchange that predated the pandemic. Multiple groups relied on prior relationships and weekly meetings with hospitals to monitor COVID-19 hospitalizations. Several reported using private emergency preparedness resources (e.g., EMResource by Juvare(11)). Some also utilized public hospitalization data sources provided by federal agencies, like the Health and Human Services (HHS) National Healthcare Safety Network COVID-19 hospitalization datasets, reported and forecasted hospitalizations from CDC, as well as CDC’s COVID-19 community levels maps, which included hospitalizations (12). Some interviewees also reported using publicly available non-federal data sources like the Hopkins COVID-19 Dashboard (13) and resources compiled by media.

Tracking COVID-19 hospitalizations presented several challenges for public health officials, including patients being transferred out of jurisdiction for higher level care, discrepancies between data sources, and missing key demographic information. Some states were able to identify the county of residence for hospitalized patients, while others lacked access to that information and were unable to accurately determine levels of disease severity by county. COVID-19 hospitalization estimates varied between state surveillance systems and federal data sources. One interviewee was under the impression that reporting was limited across states. Another discussed the challenge of data discordance: when estimates for COVID-19 hospitalizations from the internal state surveillance systems did not align with HHS estimates. In both cases, the interviewees described trusting federal data sources less. Delays in getting data were another challenge. One group was limited to annual reports of hospitalizations and highlighted the need for more timely information. Hospitalization data frequently had poor quality or missing data on key demographic information (e.g., race and ethnicity) that is necessary to identify and monitor the impact of COVID-19 in different populations.

Most interviewee groups reported supplementing hospitalization data with a range of COVID-19 data sources, including SARS-CoV-2 case data. Multiple interviewees mentioned using information from COVID-19 case investigations, but several noted that these had either slowed or stopped completely at the time of the interviews. Syndromic surveillance (e.g., COVID-like illness reports from emergency departments) was mentioned as a supplemental resource by one group; another mentioned using the number of therapeutics ordered, vaccination rates, and other vaccine indicators as additional information on what was happening in their area. Nearly all the interviewees mentioned wanting more information on COVID-19 hospital indicators. Priority indicators included measures of COVID-19 severity including changes in hospitalization and mortality rates; length of stay specific to COVID-19 hospitalizations, and hospitalizations of patients with COVID-19 compared to hospitalizations for COVID-19.

Box 1. Challenges raised by RMW public health leaders

• Challenges interpreting COVID-19 estimates in rural regions: A region with low population density reported concerns with CDC’s community level maps noting "small denominator issues”: one to two COVID-19 hospitalizations can “kick a county into higher CDC community levels.”

• Challenges translating complex concepts of immunity to simple public health messaging.

• Challenges combatting misinformation about COVID-19, vaccines and treatments

• Challenges reconciling differences in data between local/state and federal datasets

• Challenges in interpreting COVID-19 outcome data when surveillance and reporting changed

We identified current COVID-19 priorities, gaps, and needs of public health practitioners and officials during a transitional period of the COVID-19 pandemic when vaccines were widely available, many people had been infected with SARS-CoV-2, many federal public health mandates were ending, and public attention to COVID-19 was ebbing. The practitioners we interviewed reported shifts in the scope of decision-making from public health mandates to making recommendations based on CDC guidelines; needs for improving scientific communication and support to combat misinformation; and calls for continued educational outreach on topics like vaccination and immunity. We also observed ongoing challenges related to data accessibility, and changes in funding that impact surveillance data and situational awareness of the pandemic.

The original intent of these interviews was to inform how infectious disease modeling can better aid public health departments during a pandemic response. Though many of the questions and responses touched on broader issues, we found a number of topics raised by interviewees that have important implications for infectious disease modeling. Ultimately, infectious disease models are tools that generate estimates that can provide situational awareness and inform decision-making when the estimates align with decision-maker needs. Efforts to document the use of COVID-19 models in the early phases of the pandemic by state and local public health department highlighted the need for modelers to be flexible in adapting models to the needs of public health departments (3, 4). The interviews we conducted show that decision-maker needs are continuing to evolve for more than two years into the COVID-19 pandemic, and the models continue to evolve as well. The early need for estimates of the potential impact of public health mandates such as stay at home orders has been replaced by a need to generate estimates of the potential impacts of emerging variants, particularly on hospital systems and capacity, as well as the impacts of new vaccines. We view ongoing dialogue between modelers and decision-makers as key to ensuring infectious disease models are serving public health needs. Issues related to data visualization and clear communication and dissemination to the public raised by interviewees also highlight the need for modeling outputs to be easily interpretable by decision-makers and the public.

The discussion of gaps in data access and changes in surveillance have concerning implications for model parameterization and data inputs. Real-time infectious disease models often rely on surveillance data for model calibration. The noted changes to at-home testing and case reporting posed challenges for many modeling teams that relied on case reporting. Recent efforts to provide guidelines for infectious disease modeling reproducibility and transparency (14) may aid in future collaborations and may help to improve the scientific interface and accessibility of model findings for decision-making and public audiences.

Interviewees raised concerns about continuing public health mandates; specifically, the ability to implement them locally if they were not mandated federally. This was especially true of mask mandates and work or school closures. These concerns intersect with broader issues stemming from the reduction or termination of public health emergency declarations, as highlighted by Mello and Gostin 2023 (15).

Interviewees repeatedly highlighted communication challenges, including combating misinformation, and called for tools for public health staff to aid in their discussions of complex scientific issues like immunity. These challenges highlight how misinformation and difficulties with dissemination can impact the foundational capability of health departments to educate policymakers and the public (16). At the time of our interviews, multiple Omicron subvariants had swept through populations (17) and the interviewed public health officials we interviewed noted that the public had complex questions about vaccination after infection, infection after vaccination, and the duration of immunity. They articulated the need for timely communication toolkits on these topics. This request is consistent with evidence that trust in public health agencies is linked to beliefs that leaders are following scientific evidence and that guidance is evolving in response to the science (18). To combat misinformation and build trust in public health leadership, communication guides should be updated regularly and disseminated to local and regional public health leaders.

Interviewees from the RMW region highlighted aspects of surveillance that continue to be a challenge in assessing trends in COVID-19 hospitalizations and spread. They underscored how challenges of interoperability, lack of timeliness, and changing reliability of data continue two to three years into the pandemic. These gaps in surveillance directly impact emergency preparedness and response (e.g., data collection and reporting); assessment and surveillance (e.g., testing and tracing capacity); the capabilities of local and state public health departments to coordinate their response; and the delayed identification of health inequities and evaluation of trends over time. Recent investments in public health data modernization through the CARES Act and American Rescue Plan will be necessary to build on the success of improving interoperability in the healthcare sector with the 21st Century Cures Act (19, 20). Preparedness for future public health threats depends on coordinated systems within the public health surveillance system and with external partners (e.g., healthcare, emergency response). Time required to transfer data between systems reduces the time public health practitioners can spend interviewing cases and contact tracing in order to capture information on social factors that may help identify communities or individuals at higher risk of infection and severe outcomes (21).

We had a limited sample size, and our sample may not be representative of the RMW region due to lack of participation by all states. One of the challenges in recruiting participants was the high number of officials who were either out of the office or had left their position. That also speaks to the larger issue of politization of public health, safety risks (22), and burnout experienced by public health officials during the pandemic (23, 24). Despite this challenge, we were able to include representatives from state, regional, tribal and local public health agencies. We aimed to evaluate interviewee responses descriptively but did not record interviews in an effort to promote candid responses and did not apply formal qualitative approaches to our analysis. Therefore, we did not have transcribed responses and may have missed important findings.

The Rocky Mountain West region is geographically large and diverse in its population size, connectivity, and public health needs. Our study of semi-structured interviews with six convenience-sampled public health organizations identified common priorities like increasing vaccine uptake, monitoring emerging variants, and anticipating increases in COVID-19 hospital demand, but also that their capacity to meet these priorities varied. The recent termination of the Public Health Emergency for COVID-19 (25) signals a shift away from response-based activities, but also changes many of the underlying surveillance mechanisms of COVID-19 (26). We found that an ongoing challenge reported by our interviewees was access to timely, COVID-19 data, including data for vulnerable populations. These findings highlight ongoing gaps in surveillance that also impact public health preparedness for future pandemics. Concerns raised about misinformation, difficulties in implementing mandates, surveillance gaps, and needing more support and resources for science communication also underscore the need to continue funding and expanding the foundational capabilities of public health departments.

CDC, Centers for Disease Control and Prevention

COVID-19, Coronavirus Disease 2019

HHS, Health and Human Services

RMW, Rocky Mountain West

SARS-CoV-2, Severe Acute Respiratory Syndrome Coronavirus 2

Ethics approval and consent to participate. This project was carried out as a program evaluation and did not meet the definitions of research per US Department of Health and Human Services regulations.

Consent for publication

Availability of data and materials. The survey questions are provided in the manuscript. To protect the privacy of the interviewees, interview responses are not made public. Redacted versions can be made available upon request to the corresponding author.

Competing interest statement TMQ serves on the Child Trends COVID-19 Health Equity Community Advisory Board. All other authors declare no competing interests.

Funding This work was supported by Cooperative Agreement number NU38OT000297 from The Centers for Disease Control and Prevention (CDC) and CSTE and does not necessarily represent the views of CDC and CSTE.

Author contributions: TMQ, IK, EJC wrote manuscript; EJW, EJC, TMQ designed and conducted interviews; all authors contributed to editing and reviewing the manuscript.

Acknowledgements

We thank Kaitlyn Whitney for her assistance in conducting interviews and compiling survey results. We would also like to thank the public health practitioners who gave their time to participate in these interviews.

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Competing interest reported. TMQ serves on the Child Trends COVID-19 Health Equity Community Advisory Board. All other authors declare no competing interests.

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Rocky Mountain West COVID-19 Modeling: A descriptive assessment of the current public health needs during the COVID-19 pandemic to endemic transition

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Abstract

Introduction

Methods

Study Design and Recruitment Approach

Structure of Interview

Interviewee characteristics

Descriptive Analysis

Results

Current COVID-19 priorities

Current and anticipated COVID-19 decision-making

Strategies for detecting travel-associated cases and emerging variants

Monitoring of COVID-19 hospitalizations and other data sources

Discussion

Conclusion

Abbreviations

Declarations

References

Additional Declarations

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