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. 2023 Jun 14;35:102282. doi: 10.1016/j.pmedr.2023.102282

Preparing for the next outbreak: A review of indices measuring outbreak preparedness, vulnerability, and resilience

Christopher J Rogers a,b, Blayne Cutler a, Kasturi Bhamidipati a,c, Jo Kay Ghosh a,⁎
PMCID: PMC10264331  PMID: 37333424

Highlights

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    Outbreak preparedness indices vary by their geographical unit of analysis and the types of measures included.

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    Existing local-level indices mostly measure vulnerability to natural disasters or specific diseases, such as COVID-19.

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    Few indices assess local-level metrics applicable to future communicable disease outbreaks.

Keywords: Outbreak, Resilience, Preparedness, Vulnerability, Index

Abstract

The COVID-19 pandemic has highlighted the need for relevant metrics describing the resources and community attributes that affect the impact of communicable disease outbreaks. Such tools can help inform policy, assess change, and identify gaps to potentially reduce the negative outcomes of future outbreaks. The present review was designed to identify available indices to assess communicable disease outbreak preparedness, vulnerability, or resilience, including articles describing an index or scale developed to address disasters or emergencies which could be applied to addressing a future outbreak. This review assesses the landscape of indices available, with a particular focus on tools assessing local-level attributes. This systematic review yielded 59 unique indices applicable to assessing communicable disease outbreaks through the lens of preparedness, vulnerability, or resilience. However, despite the large number of tools identified, only 3 of these indices assessed factors at the local level and were generalizable to different types of outbreaks. Given the influence of local resources and community attributes on a wide range of communicable disease outcomes, there is a need for local-level tools that can be applied broadly to various types of outbreaks. Such tools should assess both current and long-term changes in outbreak preparedness with the intent to identify gaps, inform local-level decision makers, public policy, and future response to current and novel outbreaks.

1. Introduction

Over the past 20 years, there have been calls to assess public health preparedness for outbreaks and other emergencies that could befall the populations of the United States (U.S.) and countries around the world (Nelson et al., 2007a). Prior studies have highlighted the need for relevant frameworks or metrics to assess whether investments in health systems have resulted in countries that are better prepared to weather a natural disaster or health emergency. To this end, researchers and health agencies have sought to define and quantify the complex concepts of preparedness, vulnerability, and/or resilience to outbreaks or other emergencies to provide useful tools for policy design and decision-making (Kaiser et al., 2021). While each of these three concepts is critical to examine, there is no consensus definition for these terms, leading to some degree of overlap and ambiguity related to these concepts (Lei et al., 2014, Reghezza-Zitt and Rufat, 2019). Preparedness has been defined as a continuous process of anticipating emergency events, taking steps to prevent or mitigate negative outcomes, and building the capacities and resources needed to respond to and recover from such events (U.S. Federal Emergency Management Agency. , 2022, World Health Organization, 2017). Some definitions also specify types of entities needed to demonstrate these capabilities or acquire resources for certain types of preparedness; these entities include public health systems, healthcare organizations, employers or businesses, academic institutions, communities and individuals (Leinhos et al., 2014, Nelson et al., 2007b). Preparedness activities may include enhancing systems for disease detection and investigation, developing response plans for the activities needed to minimize the impacts of an outbreak, and having systems to distribute human, material, and financial resources to support public health infrastructure and ensure adequate response (Fatiregun and Isere, 2017, Freedman et al., 2013). The National Institute of Allergy and Infectious Diseases identified preclinical research and translational and clinical research as critical contributors to outbreak preparedness, as well as cross-cutting efforts such as epidemiology and pathogen discovery, technology, infrastructure, and coordination and communication (National Institute of Allergy and Infectious Diseases, 2021). Resilience has often been defined as the ability to adapt or respond to challenges and reducing or managing risks (Kimber, 2019, Wiig et al., 2020). Resilience can be applied to individuals, communities, or systems challenged during these disasters, with each of these emphasizing the ability of these entities to make changes toward improving their adaptability to challenges (Adini and Kimhi, 2023, Forcellini, 2022, Kimber, 2019, Suleimany et al., 2022). In the context of outbreaks, resilience can be interpreted as the capacity of institutions, communities, and/or individuals to effectively respond and adapt to health threats to maintain or restore themselves to the previous state (Kruk et al., 2015, Suleimany et al., 2022). The World Health Organization has suggested that outbreak resilience includes having resilient information systems, healthcare workforce, healthcare financing, as well as governance and values (World Health Organization, 2007). Emergency preparedness activities and investments may build the resilience of public health and healthcare systems to allow systems to respond more quickly to mitigate an outbreak’s impacts (World Health Organization, 2017). Communities can also improve resilience through building social capital through interpersonal networks as well as linkages with local institutions (Aldrich and Sim, 2021, Stevenson et al., 2021). Finally, vulnerability refers to conditions that affect the susceptibility of a person or community to experience harm from a negative incident, and includes internal (e.g. age) and external factors (e.g. socioeconomic position) (Clark and Preto, 2018, Cutter, 2018, de Groot et al., 2019). In many ways, vulnerability is closely related to resilience, in that both concepts describe the response to an external stressor, but resilience studies tend to focus on the impact on whole systems whereas vulnerability studies tend to focus on the impact of individual units, such as a social group or sector (Miller et al., 2010). Community vulnerability to outbreaks include population health or socioeconomic factors that increase a community’s risk of morbidity or mortality (Cutter, 2018, Flanagan et al., 2011, Sam, 2020). Given that every community must prepare for hazards and that resilience is adaptation from past hazards, vulnerability can be described as a measure of potential risk of exposure to outbreaks and the risk of consequences from outbreaks. Factors such as poverty, transportation, and crowding have been identified as links that may weaken a community’s ability to prevent consequences such as suffering and financial loss due to an outbreak (Centers for Disease Control and Prevention, 2022a). Despite the ambiguity in definitions of preparedness, vulnerability, and resilience (hereby referred to collectively as PVR), all three concepts are important in outbreak impact assessment.

One of the potential strengths of an outbreak assessment tool is the ability to identify gaps in PVR that can be addressed to prevent future impact of an outbreak on a community. Many of the tools that have been created are composite indices because of their ability to condense complex frameworks and measures into a single metric. Although an index provides value in guiding policy to pursue intervention(s) and funding/resource allocations, one noted criticism is that many indicators are never fully tested because utility and performance cannot always be directly measurable (Kaiser et al., 2021). Each index may evaluate different sets of metrics that are components of PVR. Some of the critical areas for evaluation are public health systems and capacity (Nelson et al., 2007a), health system preparedness (Palagyi et al., 2019), as well as social and economic factors that contribute to vulnerability or resilience of a community or region (Beccari, 2016, Ostadtaghizadeh et al., 2015). Furthermore, each index may focus on different outcomes. For example, some disaster/emergency indices focus on a specific type of disaster (e.g., hurricanes or earthquakes) while others capture a broader range of preparedness spheres within a composite measure.

The COVID-19 pandemic has renewed the call for improved frameworks/metrics of preparedness to inform policy, and researchers have started to evaluate available tools (Haeberer et al., 2021). One challenge in developing indices that seek to quantify some aspect(s) of PVR is the applicability of specific indicators can vary widely depending on the type of emergency affecting the population being assessed. To capture the broadest range of metrics across many types of events, some indices may lose sensitivity when compared against specific events, such as the COVID-19 pandemic or the recent mpox outbreak. Other sources of performance variability may be derived from indicators that are unique to each index, such as the domains/concepts captured by the index, the way the index was created or tested, and the spatial granularity measured (e.g., aggregated by local community, state/province or country) (Beccari, 2016).

Most prior reviews identifying emergency or disaster-related indices have assessed either preparedness, vulnerability, or resilience and its application to a broad range of emergencies or disasters (Cai et al., 2018, Fatemi et al., 2017, Heidaranlu et al., 2015, Lettieri et al., 2009, Ostadtaghizadeh et al., 2015). The gap in the review landscape is understanding PVR broadly across different types of outbreaks and spatial aggregation units. The primary goal of the current review is to identify indices that may be applied to future outbreaks and that are designed to be measured at the community (e.g., county) or regional level, rather than at the state/province or national level. The benefits of conducting this review are to highlight the existing tools that can be used in future assessments, as well as to identify some of the overlap and gaps in indices that are currently available. The review is not designed to rank the performance of the indices, but rather to identify what indices are available to use for communicable disease outbreak PVR assessment, and to suggest some strengths, weaknesses, and gaps of these current tools.

2. Materials and methods

In March 2022, indices were identified through a PubMed search, and information about relevant tools was abstracted from published manuscripts. Search terms were not date-restricted, and the final manuscripts included data from 2003 to 2022. The search strategy included terms for PVR (“resilience” or “vulnerability” or “preparedness” or “readiness”) combined with (using “and”) emergency terms (“emergency” or “disaster” or “outbreak” or “epidemic” or “pandemic”) and tool-related terms (“index,” or “rank,” or “scale,” or “score”). These terms were used to search titles, abstracts, and keywords. The study was reviewed by the Salus Institutional Review Board and determined not to be human subjects research.

Prior to review, the following inclusion criteria were established: 1. Included articles must use or describe an index or scale; 2. The index or scale must be able to be applied to an outbreak or specifically consider outbreaks; 3. The index or scale must measure some form of outbreak or disaster/emergency PVR; and 4. The article must consider an actual index in use or in development and not merely a framework. Data were extracted for organization and information synthesis using a matrix that included: title, authors, year of publication, type of article, as well as information about the index, including unit of measure(s), topic focus area(s), and whether the index specifically considered outbreaks. The matrix organization method provides a clear and concise way to cluster and summarize results of multiple studies (Garrard, 2020). The process included a title review followed by an abstract review, and a full text review. Duplicate articles were removed in the title and abstract review. Although this review aimed to identify indices pertinent to outbreak PVR, we included a broad range of indices measuring emergency preparedness and disaster vulnerability or resilience, since some components of these indices are typically also pertinent to preparedness or health outcomes related to outbreaks. Given the focus of our review on understanding local level outbreak PVR indices, any indices that fit the criteria of assessing local-level outbreak PVR from a disease-agnostic standpoint were examined further for details on their component measures.

3. Results

In total, 3,071 records were extracted, and an initial title review was conducted. Based on title screening, 2,845 articles were removed, resulting in a total of 226 records for abstract review to identify unique indices and scales. Based on the abstract review, 126 manuscripts were identified for a full-text review. In the full-text review, we removed 27 manuscripts due to covering a repeat index, 21 review articles that did not contain a new index not already covered, 11 articles that did not include a scale or index, 4 articles reporting on indices measured at the individual person level, and 4 articles that were not directly applicable to resilience, vulnerability, or preparedness. This process yielded 59 unique indices. Fig. 1. The flow diagram for study review process (Page et al., 2021) elaborates on the literature selection process.

Fig. 1.

Fig. 1

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Flow diagram for study review process.

The 59 tools identified are summarized in Table 1. The majority (n = 45, 76%) of the indices were used for local-level assessment, and the remainder aggregated data by country (n = 13, 22%) or state (n = 1, 2%). There was variability in local-level of measurement with some aggregating to a county level, neighborhood level, or even to regions serviced by a specific health center. The majority of the country-level indices were designed to compare multiple international states, with the exception of one index that was designed to track temporal trends within a single country (Kimhi et al., 2021). Among indices used for local- or state-level assessment, the majority were developed in countries other than the U.S. (n = 27, 59%), with 19 indices (41%) developed for or applied to U.S. populations. We reviewed the indices domains, subdomains, and measures to identify whether they included elements explicitly applicable to outbreaks, such as metrics of infectious disease incidence, epidemiology staffing, laboratory testing capacity, and healthcare outbreak response. A majority (n = 37, 63%) of the indices included one or more metrics related to assessing outbreaks. The remainder (n = 22, 37%) did not specifically include metrics related to assessing outbreaks; however, the tools were determined to be relevant to outbreak preparedness because they measured other social factors that are correlated with health outcomes related to outbreaks, such as disaster management, hospital preparedness, or community health and social vulnerability. Of the 37 indices that included outbreak-specific metrics, a majority (n = 27, 73%) were tied to a single disease, such as COVID-19, HIV, or influenza, because they included metrics that were measures of performance related to that specific disease. Only 10 (27%) of the 37 indices were generalized to any type of communicable disease outbreak and not specifically tied to one disease. Since preparedness, vulnerability, and resilience are distinct types of assessments, despite some ambiguity in the definitions and some overlap in the types of contributing factors, we identified the specific assessment category based on the authors’ given descriptions of the index. A majority of the indices focused on vulnerability (n = 35, 59%), while others focused on resilience (n = 14, 24%) or preparedness (n = 10, 17%). In addition to the thematic elements, the indices also differed in terms of the outcome value produced. Three quarters of the indices used a numerical score as the final metric (n = 45, 76%). The remaining indices produced a rank (n = 6, 10%), percentage or percentile (n = 5, 8%), and classes or categories (n = 3, 5%). We assessed whether the proportion of indices assessing local-level or country-level characteristics differed based on the whether the index assessed preparedness, vulnerability, or resilience. While many scales assessed local-level vulnerability (n = 29), there were 4 local-level scales and 5 country-level scales assessing preparedness. A chi-squared test of independence indicated that there were greater than expected proportions of preparedness scales represented at the country level relative to the local level and the proportions of other classes were not significantly different (χ2 = 7.591p = 0.022).

Table 1.

Key features of index tools available to measure preparedness, vulnerability, or resilience for emergencies and/or outbreaks.

Index Name Geographic Aggregation Level Country where Index is Applied Inclusion of Outbreak Measures Application to general or specific outbreaks Assessment Category Outcome Measure
Country-level Indices
Epidemic Preparedness Index (Oppenheim et al., 2019) Country NA Yes General Preparedness Score
Epidemic Risk Index – ERI (Doherty et al., 2018) Country NA Yes General Vulnerability Score
Global Environmental Vulnerability Index (EVI) / Global Focus Model / Global Risk Dashboard (Tvaronavičienė, 2021) Country NA No NA Vulnerability Score
Global Health Security Index (Abbey et al., 2020) Country NA Yes General Preparedness Rank
Holistic Resilience Index (Pileggi, 2022) Country NA Yes General Resilience Score
Infectious Disease Vulnerability Index (Moore et al., 2017) Country NA Yes General Vulnerability Score
Joint External Evaluation (Gupta et al., 2018) Country NA Yes General Preparedness Score
National Inventory of Core Capabilities for Pandemic Influenza Preparedness and Response (MacDonald et al., 2014) Country NA Yes Specific Preparedness Categorical Classes
National Resilience (NR) (Kimhi et al., 2021) Country Israel Yes Specific Resilience Score
Pandemic Efficiency Index (PEI) (Salihu et al., 2020) Country NA Yes Specific Preparedness Score
Pandemic Risk Exposure Measurement (PREM) (Grima et al., 2021) Country NA Yes Specific Vulnerability Score
Prevalent Vulnerability Index (PVI) (Cardona, 2005) Country NA No NA Vulnerability Score
World Risk Index (Welle & Birkmann, 2015) Country NA No NA Vulnerability Score
Sub-Country Level Indices
Africa
Community impact score (CIS) (Asare-Kyei et al., 2017) Local Ghana, Burkina Faso, Benin No NA Vulnerability Score
District Social Vulnerability Index (DSVI) (Dintwa et al., 2019) Local Botswana No NA Vulnerability Rank
Social Epidemiological Vulnerability Index (SEVI) for COVID-19 (Macharia et al., 2020) Local Kenya Yes Specific Vulnerability Score
Social Vulnerability Classification (Stanturf et al., 2015) Local Liberia Yes Specific Vulnerability Score
Spatially Explicit Index of Social Vulnerability (Lawal & Arokoyu, 2015) Local Nigeria No NA Vulnerability Score
Asia
City safety resilience evaluation model (Pei et al., 2019) Local China No NA Resilience Score
COVID Vulnerability Index (Mishra et al., 2020) Local India Yes Specific Vulnerability Score
Disaster-resilient communities (Kafle, 2012) Local Indonesia No NA Resilience Rank
Hazard Vulnerability Analysis (HVA) (Li et al., 2021) Local - Hospital China Yes Specific Vulnerability Score
Hollnagel’s resilience assessment grid (RAG) (Chuang et al., 2020) Local - Hospital Taiwan No NA Resilience Rank
Neighborhood Pandemic Resilience Index (NPRI) (Lak et al., 2021) Local Iran Yes General Resilience Score
Regional Vulnerability Index (Gao et al., 2021) Local China Yes Specific Vulnerability Rank
Resilience Assessment of Complex Urban Public Spaces (Xu et al., 2020) urban public spaces China No NA Resilience Score
Social Vulnerability (Zhou et al., 2014) Local China No NA Vulnerability Score
Socio-environmental Vulnerability Index (Sarkar & Chouhan, 2021) Local India Yes Specific Vulnerability Score
Vulnerability index for COVID-19 (Acharya & Porwal, 2020) Local India Yes Specific Vulnerability Score
Europe
Conjoint Community Resiliency Assessment Measure (CCRAM) (Leykin et al., 2013) Local Israel No NA Resilience Score
COVID-19 vulnerability mapping (Shadeed & Alawna, 2021) Local Palestine Yes Specific Vulnerability Categorical Classes
Multivariate Methods and Models (Davino et al., 2021) Local Italy No NA Vulnerability Score
Neighborhood Influenza Susceptibility Index (NISI) (Timpka et al., 2010) Local Sweden Yes Specific Vulnerability Percentage
Population Vulnerability to the SARS-CoV-2 (Mitrică et al., 2021) Local Romania Yes Specific Vulnerability Score
Small Area Vulnerability Index (SAVI) (Daras et al., 2021) Local United Kingdom Yes Specific Vulnerability Score
North America
Assessment for Disaster Engagement with Partners Tool (ADEPT) (Glik et al., 2014) Local US No NA Preparedness Score
Baseline Resilience Indicators for Communities (BRIC) (Cutter et al., 2010) Local US No NA Resilience Score
Community Disaster Resilience Index (CDRI) (Peacock et al., 2010) Local US No NA Resilience Score
Community Resilience Estimates (Dick, 2022) Local US No NA Resilience Percentage
Community Resilience Index (CRI) (Sherrieb et al., 2010) Local US No NA Resilience Score
COVID-19 Community Vulnerability Index (Surgo Ventures, 2020) Local US Yes Specific Vulnerability Rank
COVID-19 Vulnerability Index (C19VI) (Tiwari et al., 2021) Local US Yes Specific Vulnerability Score
COVID-19 Pandemic Vulnerability Index (PVI) (Marvel et al., 2021) Local US Yes Specific Vulnerability Score
Data-driven complex systems modeling (Yabe et al., 2022) Local US No NA Resilience Score
Hospital Medical Surge Preparedness Index (HMSPI) (Marcozzi et al., 2020) Local - Hospital US Yes General Preparedness Score
National Health Security Preparedness Index (NHSPI) (Lumpkin et al., 2013) State US Yes General Preparedness Score
Racial, Economic and Health Inequality (Abedi et al., 2021) Local US Yes Specific Vulnerability Score
Rapid Urban Health Security Assessment (RUHSA) (Boyce & Katz, 2020) Local US Yes General Preparedness Categorical Classes
Social Vulnerability Index (SoVI) (Cutter et al., 2003) Local US No NA Vulnerability Score
Social Vulnerability Index (SVI) (Flanagan et al., 2011) Local US No NA Vulnerability Rank
Time-varying vulnerability index (county‐level vulnerability index) (Gorris et al., 2021) Local US Yes Specific Vulnerability Score
US county-level COVID19 vulnerability (Cahill et al., 2021) Local US Yes Specific Vulnerability Percentage
VILLAGE Project (Vulnerability Investigation of underlying Local risk And Geographic Events) (Yedinak et al., 2021) Local US Yes Specific Vulnerability Score
Vulnerability score (Bergo et al., 2021) Local US Yes Specific Vulnerability Score
Oceana
Australian National Disaster Resilience Index (ANDRI) (Parsons & Morley, 2017) Local Australia No NA Resilience Score
COVID-19 Pandemic Vulnerability Index (CPVI) (Saghapour et al., 2021) Local Australia Yes Specific Preparedness Score
South America
Aedes aegypti-vectored disease Vulnerability (Meisner et al., 2021) Local Peru Yes Specific Vulnerability Score
COVID Health Structure Index (Ferraz et al., 2021) Local Brazil Yes Specific Vulnerability Score
IndCo (Almeida et al., 2020) Local Brazil Yes Specific Vulnerability Score
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Note: The citations are from the articles in which the index was found in the review process. Some of the indices also have their own citations beyond the article that is presented in this review. Assessment categories were individually defined and specified by the authors of the manuscripts they were abstracted from and were not recategorized for this review.

Among indices that included specific outbreak elements, the majority assessed local-level or hospital-level PVR (n = 26, 70%), among which 18 indices focused on COVID-19 specifically. Among the 10 indices with outbreak-related elements that were more broadly applicable to different types of outbreaks, six of these indices were designed to compare pandemic-related factors across different countries. These country-level indices typically included measures assessing national-level economic and financial resources, along with healthcare and public health systems and infrastructure. Some of these country-level indices also included measures of political stability, demographic risk factors (e.g., age or chronic disease prevalence), and social risk factors (e.g., unemployment or aid dependency).

Given that the focus of the review was to assess local-level PVR to future outbreaks, we sought to describe the domain structure and capabilities assessed in the three indices identified that measured PVR at the local/community level and were applicable to any type of outbreak. These three indices were the Rapid Urban Health Security Assessment (RUHSA) (Boyce & Katz, 2020), the Hospital Medical Surge Preparedness Index (HMSPI) (Marcozzi et al., 2020), and the Neighborhood Pandemic Resilience Index (NPRI) (Lak et al., 2021).

The RUHSA is a preparedness capabilities assessment tool developed for local government leaders and is comprised of four domains. The domains are organized based on the stage of preparedness activities (prevention, detection, response, and other). Within the “Preventing Public Health Emergencies” domain, the tool assesses legal and policy frameworks, financing and resources, coordination and communication, and immunizations. The second domain, “Detecting Public Health Emergencies”, encompasses laboratory systems, surveillance systems, disease reporting and human resources. Under “Responding to Public Health Emergencies”, the tool assesses emergency preparedness, emergency response, non-pharmaceutical interventions, health care delivery, risk communication, human resources, and recovery and rehabilitation. The final domain is for “Other Considerations”, which encompasses points of entry, mass gatherings, and specific hazard surveillance and response plans.

The HMSPI focuses specifically on hospital preparedness capabilities and is organized into four domains based on surge capacity: “Space,” “Staff,” “Supplies,” and “Systems.” The “Space” domain assesses facility, storage, and laboratory capacity, such as total staffed beds and spaces that could be made available to accommodate a surge of patients. The “Staff” domain assesses the numbers, expertise and stamina of personnel, such as nurses, physicians, technicians and non-medical personnel at facilities. The “Supplies” domain identifies availability of both durable equipment (e.g., cardiac monitors, respirators, laboratory equipment) as well as consumable materials (e.g., personal protective equipment, syringes, catheters). Finally, the “Systems” domain assesses organizational policies and procedures pertinent to surge planning, including procedures for interacting with other healthcare entities, such as long-term care and emergency medical services organizations.

The NPRI focuses on the environmental and demographic aspects of infectious disease resilience among neighborhoods in Tehran and is organized into six domains which reduced into four dimensions based on the results of their Principal Components Analysis. The “Physical Dimension” incorporated measures of the built environment, such as the number of hospitals, clinics, chain stores, and supermarkets in the neighborhood, and the degree of housing land use. The “Infrastructural Dimension” assessed access to health centers and public transportation, as well as population density. The “Socio-economic Dimension” included measures of land use mix, the quality of the residential areas, poverty and unemployment levels, elderly population, and measures of neighborhood and social capital. Finally, the “Environmental Dimension” included measures of pollution, building density, open space, and meteorological factors.

The three indices presented above not only included different domains but also had key differences in data availability, application, and the way the indices were calculated; these features are summarized in Table 2. Two of the three indices used only publicly available data to calculate the index; the third index used a private paid access dataset from a professional association. Both can be recreated using original data sources; however, one is specific to Tehran and the other is focused on hospitals and hospital catchment areas. The final index provides a framework and clear criteria for calculating a local level index; however, data need to be collected from each city or municipality individually and are not currently publicly available on a wide scale. While all three of these indices consider the healthcare system capacity and/or access to healthcare facilities, only the NPRI considers community demographics, along with social and environmental factors. Furthermore, the RUHSA—focused on urban locations—is the only one of these tools considering public health system capacity. All these factors are important considerations when thinking about local level outbreak PVR. Therefore, there is a need for a tool that is broadly applicable to communicable disease outbreaks, measured at the community level, and considers multiple domains of healthcare systems, public health, social systems, and the underlying population factors contributing to community vulnerability.

Table 2.

Detailed features of three identified indices that measure preparedness, vulnerability, or resilience at the local/community level and were applicable to any type of outbreak.

Domains or Constructs Data Types Index Calculation Data Availability Application Most Recent Data
Rapid Urban Health Security Assessment (RUHSA) (Boyce & Katz, 2020) The focus is on cities and municipalities and the included domains are: Prevention, Detection, Response, and Other Considerations A framework and data are to be collected by cities. Questions are scored by evaluators on a 1–3 Likert scale. Indicators have detailed explanations for users to help score each value. Each capacity is meant to be assessed individually; however, categories (domains) can be summed or scored. Data are not currently collected across wide regions. Cities and municipalities can use this framework to collect data. The framework was framework presented at the 2019 Annual
Summit of the Global Parliament of Mayors and the tool is available for local municipalities to use.		 Given how new the tool is there is limited data on its application within cities and municipalities.
Hospital Medical Surge Preparedness Index (HMSPI) (Marcozzi et al., 2020) The focus is on hospitals and health care centers and the included domains are: Prevention, Space, Staff, Supplies, and Systems Most of the data are counts of staff, beds, and equipment/supplies but also include measures of size as well as binary and ordinal questions related to systems, planning, and coordination. Since different questions can produce different values or data ranges, individual item scores were normalized and then sub-domain scores were normalized. A total score was calculated and then the score is then meant to be per capita
ratios for each geographic unit (hospital catchment area). This is calculated as the Score per unit divided by the total population in the service area of that unit.		 Data are collected from the American Hospital Association’s (AHA) annual survey, as well as data from the
U.S. Census Bureau and the Dartmouth
Atlas Project.		 The sample used for the initial index used local hospital level data from 6,239 hospitals across all 50 states. The most recent data provided within the articles included used AHA data from 2005 to 2014
Neighborhood Pandemic Resilience Index (NPRI) (Lak et al., 2021). The focus is on neighborhoods and the included domains are: Prevention, Physical, Infrastructural, Socio-economic, and Environmental Most of the indicators are either percentage of the population, counts of the population, amounts of exposures and ratios of the population. Individual indicators are normalized and weighted. Scores are calculated based on based on their standard deviations from the mean. Uses 2017 population and housing
census data of Tehran.		 The initial application so far has been in Tehran. The most recent version uses 2017 population and housing
census data of Tehran
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4. Discussion

The COVID-19 pandemic and other recent communicable disease outbreaks have highlighted the need to enhance outbreak preparedness, including ways to track and assess contributing local resources and community attributes. A set of core metrics should be able to capture outbreak PVR in a community and accurately convey areas that need additional support with preparedness resources. Identification of existing tools for the assessment of outbreak PVR is a critical step in identifying potential gaps that need to be addressed to support capacity building in this arena. This review was designed to identify existing resilience, preparedness, or vulnerability indices that are applicable to outbreaks and are measured at the community/regional level. Overall, the literature search identified 59 available tools that may be applied to outbreak PVR. The majority of the indices were focused on vulnerability or resilience, with a smaller number focusing on preparedness. Most of the indices/scales were identified through the initial data capture through studies that explained the creation or testing of the index. Additional tools were identified through supplemental reviews of specific aspects of emergency preparedness.

A large proportion of the tools identified considered local-level measures, suggesting that there are many options for assessing PVR at the local level, though the focus of these tools differ considerably based on the metrics used. The remaining tools were designed to capture state- or country-level aggregated data. In addition, among indices assessing preparedness, the number of indices measuring country level indicators was significantly higher than the number measuring local-level indicators. The types of measures used in the country-level indices, such as macro-economic factors, may not be applicable to local-level preparedness assessments, which focus on resources and capabilities available in the local region. This reveals a need for more indices to be disaggregated to local-level measurement and specifically for more preparedness indices that can further inform public health actions toward the next outbreak.

Most of the tools did include some metrics for assessing outbreaks, however, most were focused on ascertaining PVR for a single disease. These tools typically used specific disease-related outcomes as an indicator within the index (e.g., case rates or cause-specific mortality rates). Using disease-specific metrics may create a strong indicator of performance when the index is meant to be focused on that one disease, rather than overall preparedness; however, prior reviews noted that indices intended to assess general preparedness (not a specific single outbreak) were not as accurate in the predictions of COVID-19 outcomes (Kaiser et al., 2021). Even though disease-specific indices are important, we will not always have these specific indices for new and emerging disease outbreaks and, as such, general outbreak preparedness indices are still relevant. Although the current review did not assess the application of these metrics, an interesting pattern has emerged regarding these tools. A large majority of the indices assessing general outbreak PVR were applied or designed at the country level, whereas metrics that aggregated data at the local level were typically tailored to a specific disease. The scarcity of local-level tools for general outbreak PVR may be a critical area of need to address in future indices. Aggregation at the country level may lose much of the granularity for preparedness that takes place at the local jurisdiction (Birkmann, 2007). While federal-level metrics are important for improving outbreak PVR, much of the work of outbreak response in the U.S. typically occurs at the local level because of the nation’s public health structure, where state and local jurisdictions have considerable public health authority and responsibility, pointing to the importance of local level capabilities.

Within the U.S., there is variability in the way outbreak preparedness is operationalized across the country. While federal programs currently provide the bulk of preparedness funding, many of these funds are managed at state and local public health agencies, as well as within both public and private healthcare organizations (Assistant Secretary for Preparedness and Response, 2021, Centers for Disease Control and Prevention, 2022b). Although federal programs funding preparedness activities require grantees to adhere to the program requirements, this decentralized structure allows for tremendous variability across regions based on the capacity and capabilities of the health systems within a specific jurisdiction. Because of the variability created by a patchwork of public and private health systems across the United States, and because county public health departments vary in their preparedness activities, local level assessment of outbreak preparedness in the U.S. may be more informative than aggregation at the state or country level. A consideration identified by this review is that there are limited indices available for assessing local-level variability in general outbreak preparedness in the U.S. Although frameworks have been proposed (Boyce & Katz, 2020), implementation across states or the country is limited. To emphasize areas for growth and to assess local level strategies to meet outbreak preparedness needs for future outbreaks, a comparable index that can assess local level outbreak preparedness across jurisdictions is needed. Such metrics provide an evidence-based assessment for improving public health outbreak preparedness and informing future response to current and novel outbreaks.

This review identified many indices that can be applied to outbreak PVR, but these indices differ widely based on their unit of analysis, types of data sources, and methods of data standardization. Some are uniquely designed for a specific region and use data only available for that region, reducing the replicability. Others focus on specific units of locality such as hospital catchment areas, neighborhoods, counties, or cities. Many of the indices primarily leverage publicly available data to calculate indicators, suggesting there is data available and a consensus that public data may be a place to start understanding outbreak PVR. Other indices do provide a framework or new tool to be used that asked specific questions of stakeholders; however, the greatest challenge of these tools is that the application of these in a wide scale can be tied to costly and time-consuming data collection efforts. These frameworks and new tools may provide a more detailed and focused look at outbreak PVR relative to publicly available data; however, more research is needed to confirm correlates of these new frameworks and public metrics as well as metrics related to future outbreaks. Finally, many of these indices employ different methods of standardization such as normalization or z-scoring on either the individual item level, domain/subdomain level or in the index summation process. This standardization does help to allow comparison across domains but maybe not across regions. One of the complications is that the underlying population structure of the region needs to be considered in cross region comparisons or even in temporal trends within the same region. All these factors may be important considerations when evaluating the applicability of different outbreak PVR indices. It is also important to consider that the inclusion of outbreak specific indices that primarily include indicators that focus on a specific disease may improve the predictive power of that index on those specific diseases, but this also reduces the applicability to other outbreaks or conditions. This review has identified three indices with the capability to assess overall outbreak PVR at the local community level. While all three indices consider the healthcare system capacity, none assess both public health system capacity and measures of community socio-demographic characteristics that contribute to disease vulnerability. Therefore, there is a need for tools that can be applied to all outbreaks, measured at the local community level, and that considers multiple domains of healthcare systems, public health, social systems, and the underlying vulnerability of the local community.

5. Limitations

While this review provides a summary of current outbreak PVR tools that are available, it does not provide in-depth evaluation on the utility of each. Rather, the primary aim of this review is to describe the landscape of the tools available for use, classifying them based on level of data aggregation and consideration of outbreaks. Future reviews may consider further exploration of domains and measures to fully evaluate the usefulness of different constellations of local level measures that can be applied to outbreak preparedness.

6. Conclusions

It is challenging for a composite index to capture outbreak PVR, and inclusion of local level metrics may help to better explain variability. To this end, there are many tools available to assess outbreak preparedness with most assessing local level variability and being tailored to specific diseases. This review provides a catalog of current outbreak PVR tools that are available and their key features, including the geographical unit of aggregation. An important consideration is the need for local level tools that can be applied much more broadly to outbreaks of various diseases and/or other public health disasters/emergencies with the intent to inform decision makers, public policy recommendations, and future responses to current and novel outbreaks.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability

No data was used for the research described in the article.

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