Major Indicators for Public Management Decision-Making during the COVID-19 Pandemic ()
1. Introduction
Global-scale health emergency situations, such as the COVID-19 Pandemic, demand collaborative and well-coordinated approaches, which also need to consider the economic and social context, phenomena empirically evidenced by society.
Based on this, the lack of dialogue between the different parties and the administration of a variety of social, economic and health factors limits the potential participation of the responsible for the response actions (Khorram-Manesh et al., 2022).
A proper response procedure in public emergencies depends on several interrelated factors. In some specific cases, such as hurricanes and earthquakes, which can be more accurately predicted through technology, vulnerable points can be previously identified and the decision-making process is supported not only by scientific models, but also by action plans implemented in preceding similar situations.
The COVID-19 Pandemic, however, involves living organisms, with a restricted prediction capability, and the impact of human behavior, political and social factors also limit the development of scientific and metric-based models, complicating the establishment of response protocols (Qiu, 2020).
Although some variables can be expected, such as standard hygiene habits always recommended by health organizations, for instance washing hands frequently and keeping physical distances, contradictory public authorities’ speeches can lead to doubt on experts’ recommendations and social-division, intensifying existing social tensions and creating scientifically immeasurable variables (Deps & Cassimiro, 2020).
Creating a response protocol to a global-scale crisis caused by a new virus as the SARS-CoV-2, one-variable models are not enough to handle the complexity of its impacts in different social fields. Ramadan et al. (2020) suggest multi-variable models for a more accurate and adequate projection of complex crisis.
A Systematic Bibliographic Review (SBR) is one of the best tools to elaborate a protocol with a scientific basis, identifying the main terms, keywords and prevalence indicators on the subject with robustness.
Therefore, the objective of this research was to identify the major indicators for the Public Management decision-making during the COVID-19 pandemic and its impacts on the population. The study was based on a Systematic Bibliographic Review (RBS) of the most relevant literature published to date.
2. Methodology
Systematic Bibliographic Review for Bibliometric Analysis
The present research is an exploratory and descriptive study, classified as survey research. Specifically, it is based on a sample survey (Gerhardt & Silveira, 2009), aimed to build new knowledge and expand the understanding of a topic, based on the collection of existing concepts and discussion through a Systematic Bibliographic Review (Pereira et al., 2018).
The data search was comprehensive without language restrictions, using the Scopus database, which is the largest database of abstracts and citations in the literature with peer review, and Science Direct, another research tool for researchers, professors, students, and Healthcare professionals.
All the entries used for search in the databases were English terms and their derivations. The language choice was based on a more comprehensive search, as the terms in English are always indexed regardless of the publication language. Table 1 shows the terms used in the Bibliographic Review.
For a more extensive investigation, a total of 18 different combinations of the terms were also used in both databases. Table 2 shows all the combinations used.
The combination of the keywords in both databases yielded a total of 14,136 results. These were analyzed in different stages, as follows. Stage 1: General research; Step 2: Selection of journal articles; Step 3: Duplicates removal; Step 4: Delimitation of publication period (2019-2022); Step 5: Reading of titles and abstracts; Step 6: Methodi Ordinatio application. Table 3 presents the results obtained in each database, including the selection process of the final articles listed for a deeper analysis.
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At the end of the search step in the databases (Step 1), the Mendeley® software was used to group and order the articles, which were then structured in Microsoft Office Excel®. Books and book chapters, conferences, congress articles and complementary results were excluded, leaving only journal articles (Step 2).
Following, duplicates, i.e., articles indexed in both databases, were excluded (Step 3). In Step 4, the publication period was delimited, selecting only articles published between 2019 and 2022, including articles not yet published but accepted for publication.
Finally, after reading the titles and abstracts (Step 5), 447 articles that were closely related to the scope and objective of the present research were selected.
In a final step, a categorical algorithm Methodi Ordinatio (Step 6) by Pagani, Kovaleski & Resende (2015) was used to order and select the most relevant articles. This algorithm considers the impact factor of the journal in which the article was published, the year of publication, in addition to the number of citations in Google Scholar, as shown in Equation (1):
. (1)
where:
: Impact Factor
: Year of search
: Publication year
: Number of citations in Google Scholar
Source: Pagani, Kovaleski & Resende (2015).
The alpha (α) is an index chosen by the authors to adjust, if necessary, the weight of a specific group for the SBR. In the present work, the same value was used for all the groups, as all share the same level of importance for the study. A graphical representation of the Methodi Ordinatio ranking application is shown in Figure 1. The X-axis shows the “Accumulated Index”—the sum of all the indexes obtained as per the Equation (1). The orange line is a graphical representation of the “Accumulated Percentage” of the results. The percentage selected by the authors defines the threshold that determines the number of articles selected for a deeper analysis. In the present research, the accumulated
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Figure 1. Number of articles selected based on Methodi Ordinatio ranking.
percentage threshold was set at 10.7%. Based on this, the total number of articles for further analysis is represented by the intersection of the red lines in the graph. In the present study, this meant 83 out of the 447 articles. A list of all the 83 articles is available in Appendix 1.
3. Results & Discussion
To elaborate a scientific model for decision making, the categorization of the collected inputs within groups based on similarity facilitates the process.
A wide variety of articles, authors, journals, and nationalities were found throughout the research. The first analysis performed was based on the keywords. The graphic in Figure 2 displays the results linked to each group of keywords.
According to the graphic, the keywords combination “Decision; COVID-19; social distancing” presented the higher number of citations among the articles analyzed. As a result, over the years, there were a greater number of publications related to these keywords combinations when compared to the others.
The analysis of the articles allowed a compilation of the different indicators for Public Management Decision-Making during the pandemic. For analysis purposes, the primary indicators identified through the Systematic Bibliographic Review were grouped into indicators considered as relevant for the decision-making process, namely: political, health, social, psychological and economic factors. These indicators are summarized in Appendix 2 and each indicator will be developed in more detail in the following sections.
The representativeness of each indicator in according to the Systematic Bibliographic Review is shown in Figure 3.
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Figure 2. Number of articles per keyword(s).
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Figure 3. Major indicator groups found in the systematic bibliographic review.
The political indicator was the most recurrent, being mentioned in 48 articles. Within this group, the primary indicator “Government conduct” stands out. The increasing concern on the subject among the scientific field highlights the importance of the government in the decision-making process, especially during global-scale crisis. At the same time, as the government also needs to ensure economic protection, there is a necessity to evaluate the impacts of extreme measures, such as lockdown.
It is also worth mentioning that the primary indicators were grouped according to their relevance within the pandemic context. Undoubtedly, political issues encompass health and social issues, but the results were grouped by similarity to facilitate the analysis. Each main group of indicators is discussed in more details in the following sections.
3.1. Political Indicators
The Federal and local Governments are responsible for ensuring the safety and health of the population. As many factors are related to the political and governmental elements, a predominance of political indicators, as found during the present research, is expected. The representativeness of each primary indicator within this group is shown in Figure 4.
An analysis of the graphic shows that the Government Conduct Indicator stands of not only as the main political indicator, but also as the major indicator for the decision-making process during COVID-19. The COVID-19 pandemic has led to reflection about how political pressures impact the population credibility on Science (Deps & Cassimiro, 2020). In fact, the government conduct, when aligned with the guidelines of the scientific field is a very important key to ensure an efficient response during crisis (Censon & Barcelos, 2020; Ney & Gonçalves, 2020).
Ney & Gonçalves (2020) point out important factors within political indicators, such as the existence of a Public Health System, as in the case of the Brazilian Unified System (in Portuguese “Sistema Unificado de Saúde”—SUS). As the authors also state, the government’s interest in promoting the access to health is one of the main factors to ensure a good response to a pandemic, which was confirmed in COVID-19.
Furthermore, when aligned with collective interests, it also contributes to adequate risk communication, with transparency about the potential damages as well as the contingency policies (Habli, Alexander, Hawkins, Sujan, McDermid, Picard, & Lawton, 2020). A proper risk communication can mitigate damage and save lives (Beccari, 2020).
The combination of different experiences, knowledge and the synergy between institutions is also essential to solve complex challenges. Strong interaction
between universities, governments, companies, and the society in general is an effective tool to minimize the impacts of future challenges, ensuring better risk management and adaptation (Amorim & Andrade, 2020).
Another important factor is the so-called response simulation, or crisis learning (Trachsler & Jong, 2020). Countries that practice disaster simulations usually respond to crisis in a much more robust and organized manner, when compared to those which lack the disaster simulations. Even without simulations, the existence of simple health response protocols can already ensure better safety for different professionals and leaders during large-scale emergencies (Coelho et al., 2020).
The decision-making process involves different fields of the society, but it remains highly dependent on the autonomy of the State. Thus, to ensure an efficient response to COVID-19, political leaders are key element, which is confirmed by the number of the countries aligned with the Science and Ethics guidelines.
3.2. Health Indicators
The Health Indicators assess the severity of the situation in a given location and evaluate the efficiency of the different responses. Figure 5 illustrates the representativeness of each primary indicator within the Health Indicators Group.
Nazari, Shahriari, Dadgarmoghaddam, Saki, Nahidi, Mehrabian & Tabesh (2020)highlight the importance of identifying non-compliance factors and analyzing
the numbers related to the pandemic to ensure effective responses. At the beginning of the pandemic, computing the number of cases and deaths and forecasting economic impacts were the first measures for a quick response while waiting for treatment and vaccines (Sciortino & Saini, 2020; Stone & Scheib, 2021). However, as the infectibility rates proved to be 50 to 85 times higher than previously thought, also dependent on the dominant virus variant, these measures proved to be insufficient (Silva, Paz, Ribeiro, Freire, Oliveira, Leite et al., 2022).
Other factors, such as the availability of tests and number of tests performed, also influence the perception of response efficiency. The number of tests must be compatible with the population size and mobility, as a relevant forecast of the number of isolated people and the number of severe cases allows a better implementation of Public Health Policies and management of available resources, such as ICU beds and respirators (Sokolov & Sokolova, 2020).
Furthermore, some metrics must be tracked with higher frequency, as epidemiology parameters can help project future cases of COVID-19, deaths, and hospitalizations and admissions to ICUs, in addition to guiding social distancing and lockdown measures (Chhatwal, Dalgic, Mueller, Adee, Xiao, Ladd, Linas, & Ayer, 2020). Moreover, infectiology-related metrics always present a fluctuating pattern. Besides the existence of asymptomatic cases, the duration and power of protective immunity after recovery and/or vaccination is not an exact measure (Habli, Alexander, Hawkins, Sujan, McDermid, Picard, & Lawton, 2020).
The investigation and projection of these data must also comply with ethical standards within the Government, both in data treatment and dealing with resources, considering possible resources and manpower scarcity and other ethical dilemma (Nomani & Parveen, 2020). The data needs to be not only carefully processed, but also transmitted in a clear and non-biased manner to the population, also stimulating social distancing and other health practices from each citizen.
3.3. Social Indicators
Although the COVID-19 pandemic is ultimately caused by a virus, it is highly influenced and determined by human and social behavior. Therefore, understanding these social factors is fundamental. In Figure 6, the representativeness of each primary indicator within the Social Indicators Group can be seen.
Intervention responses to COVID-19 go far beyond public and state power, as its occurrence is not localized nor visible or palpable. The control of an agent with rapid transmission depends on human behaviors and social variables to happen effectively (Sciortino & Saini, 2020).
One of the first factors to be considered is the social infrastructure situation of a given location. The demographics of the population exposed to the COVID-19 virus, such as mobility rate and level of basic infrastructure, dictate the effects of counter-propagation. Therefore, populations within regions with higher infrastructure levels tend to observe quicker responses to global-scale crisis (Qiu, 2020).
In addition to infrastructure, issues such as social security felt by the population directly affect human behavior involved in prevention strategies, as other problems arise when a certain population has a lockdown enacted, for example. The level of resources, urbanization, security, infrastructure and even basic issues such as access to food, drinking water, hygiene instruments also directly dictate the impacts of a respiratory virus in a given place (Rodrigues, Carpes, & Raffagnato, 2020).
In addition to infrastructure, other factors, such as social security also directly affect human behavior and prevention strategies, as other problems arise during lockdown mandates, for example. The level of resources, urbanization, security, infrastructure, and access to basic needs, including food, potable water and hygiene products are determinant in the impacts of a pandemic as well (Rodrigues, Carpes, & Raffagnato, 2020).
During the decision-making process, cultural aspects also play an important role, as the diversity and lifestyle habits of a population highly influence the acceptance and adoption of health and safety guidelines.
These factors evidence the level of vulnerability of different regions. Although the COVID-19 pandemic has affected the entire planet, its effects are experienced differently depending on the region. Management issues become more exacerbated when extreme and non-popular decisions, such as lockdown measures, are crossed with structural problems, e.g., domestic violence or lack of access to basic needs, along with mental health-related problems, as anxiety and depression rates, more pronounced during isolation (Sokolov & Sokolova, 2020).
3.4. Psychological Indicators
Individuals play an important role in accepting crisis, as the COVID-19 pandemic. The Psychological Indicators allow the understanding of common human behaviors in relation to risk and the process of human adaptation. Figure 7 shows the
representativeness of each primary indicator within the Psychological Indicators Group.
According to Sciortino & Saini (2020), the media sensationalism, broadcasting scenes of deaths and ICU patients, together with the increasing number of cases, promoted fear in the population. Although there was a need to create a sense of urgency and to stimulate people to follow safety measures and precautions, it also caused severe mental consequences among the population.
Several variables are related to why an individual or a group chooses to comply or not with individual and collective protection and prevention measures, namely: group herd behavior, the naturalization of risk and death, and the perspective of real-life risk. As the sense of risk is a non-tangible and non-measurable variables, it creates margin for disbelief (Habli, Alexander, Hawkins, Sujan, McDermid, Picard, & Lawton, 2020).
In addition to these, there are other correlated factors that influence large groups in complying with the norms imposed in response to the pandemic, such as the fear of unemployment, violence, stress, panic, and depression, which according to Becher (2020), can claim more lives than the virus itself.
The Psychological factors are subjective and fluctuating, as each society, each group and each individual behave in unique ways, which makes the impact of the pandemic more abstract, and data measurement more challenging.
Within this scenario, besides emotional adaptation, Khorram-Manesh et al. (2022) also highlight the importance of “flexible outbreak capacity” to enable collective learning in coping and to identify the most effective manners to promote conscious behavior among the population.
3.5. Economic Indicators
All global-scale crises, whether environmental or health-related, has an impact on local societies. The COVID-19 pandemic enhanced social inequality, in a phenomenon that some researchers classify as a “cascading disaster”, to refer to secondary crisis derived from a primary one. The representativeness of each primary indicator of the Economic Indicators Group is illustrated in Figure 8.
The COVID-19 pandemic feature a necessity to implement actions to reduce social inequalities, creating structures and policies that provide people and communities with the ability to create solutions in a community. When people’s basic needs are met and functioning public infrastructure and support systems, they are more likely to cooperate in unpredictable situations when disruptions to these systems occur (Thomas, Jang, & Scandlyn, 2020).
The countries have been managing the pandemic consequences differently, with the low-income population being the most affected. Mitigation efforts have also created an imbalance between the health of the population, the capacity of the health system and economic prosperity.
The COVID-19 pandemic presents potential long-term social, political, economic, and cultural impacts, in addition to the immediate consequences for the individuals. Moving from recommendations and scientific evidence to a policy decision requires policymakers to consider assumptions, risk-taking beliefs, and tradeoffs. These are often not straightforward or measurable (Habli, Alexander, Hawkins, Sujan, McDermid, Picard, & Lawton, 2020). Therefore, governments’ challenges to balance responsibility demands while rethinking policies have significantly increased (Boin, Lodge, & Luesink, 2020).
4. Final Considerations
The present study identified the most relevant indicators for the decision-making process of Public Management during the COVID-19 pandemic, but also identified the main political, health, social, psychological, and economic factors that need to be integrated for an assertive response in the epidemiological control of the COVID-19 pandemic.
In total, 24 primary indicators were identified, with Government Conduct being
the most important, mentioned in the majority of the articles analyzed. This supports the idea that the ethical and scientific responsibility of political managers at the local, federal, and international levels is essential for the protection of the population.
This research also provides inputs and resources for the elaboration of a multi-analysis modeling to assist in the decision-making process ensuring that the measures are constantly updated and adapted for each population, context and culture.
Based on the analyses carried out throughout the research, further studies to assist in the decision-making during the COVID-19 pandemic in different contexts are recommended. These studies shall deepen the understanding of the most effective measures to prepare for, and during, an emergency health crisis in different territories and also across the globe.
The contribution of the scientific community and universities, together with governments, companies, and society can optimize risk management and decision-making processes, thinking ahead to minimize the impacts of future challenges imposed by a pandemic or other large-scale crisis.
Appendix
Appendix 1. Most Relevant Articles for the Bibliographic Review
Appendix 2. Indicators and Primary Indicators