Social capital in a time of uncertainty: A case study of COVID-19 in Maharashtra state, India

Abstract

A novel coronavirus disease (COVID-19) was reported in India in late January 2020, less than 50 days after the first case was reported in Wuhan, China. Knowingly or unknowingly, almost all aspects of humankind around the world are affected, including physical, mental, and financial aspects. We set out to investigate how local communities take preventive action and have a meaningful role in dealing with these impacts of COVID-19. This community role is absolutely based on trust, regular communication, and social networking among community members. We collected data from India to determine whether the community-level response to COVID-19 during the peak phase of the pandemic (January 1st to February 1st, 2021) depended on the level of social capital. The source of information on COVID-19 is one of the significant issues during the pandemic. People prefer to depend on and trust family members, who represent the only trustworthy source of information irrespective of where they bring the information. In general, regular participation in local activities plays a major role in preventing COVID-19 at the local level.

1. Introduction

Any disaster that threatens people’s lives represents a significant burden for all those affected. After it emerged in China, the first case of coronavirus disease 2019 (COVID-19) in India was reported on January 30th, 2020, when three Indian medical students returned to Kerala in South India from Wuhan. As of the writing of this article, August 1st, 2021, the global count includes 216,867,420 confirmed cases with 4,507,837 deaths. In India, there were 32,768,880 confirmed cases and 438,560 deaths. According to insurance company claims by their customers based in Telangana state, the virus has killed six times more people than official numbers admit. The reason behind the misleading official numbers is that India’s many tiers of government, whether at the central level or under any ruling party, cannot generate solid statistics. The Disaster Management Act of GOI (2005) defines biological disasters as scenarios involving disease, disability, or death on a large scale among humans, animals, or plants due to toxins or disease caused by live organisms, plants or their products. The prevention of epidemic control does not rely on only social or geographical distancing, demography, migrators, or other factors. How local communities take preventive action also has a meaningful role. According to Kawauchi (2008) and Iwasaki (2017), a growing body of evidence has highlighted the role of social ties, trust, and interrelations during emergencies and disasters. Communities with intense relations linking social capital initially presented measurably lower levels of COVID-19 cases in Japan’s 47 prefectures (Fraser & Aldrich, 2021).

Many studies compare the 1918 Spanish flu and the current pandemic. For instance, the WHO (2009) provides the main actions in affected and nonaffected countries during the pandemic (see Table 1 ). However, in the early 20th century, territories were neither interconnected nor interdependent; this situation differs greatly from the current case of COVID-19, the nature of transmission in its fertilization period and the potential need for medical attention. As a country where 22 significant languages are used for communication, India has tried to develop its own way to support its people’s resilience and resourcefulness. In India and abroad, several criticisms, mostly unpredictable, were revealed during the pandemic. The livelihood of daily and agricultural laborers was directly affected by the nationwide lockdown, and achieving a balance between saving lives from the virus and saving livelihoods from the lockdown effects became tremendous challenges that still need to be addressed.

Table 1.

Main actions in affected and nonaffected countries.

Phase	Description	Main action in affected countries	Main action in not-yet-affected countries
1	No animal influenza virus circulating among animals has been reported to cause infection in humans.	Producing, implementing, exercising, and harmonizing national pandemic influenza preparedness and response plans with national emergency preparedness and response plans.
2	An animal influenza virus circulating in domesticated or wild animals is known to have caused infection in humans and is therefore considered a specific potential pandemic threat.
3	An animal or human-animal influenza reassortant virus has caused sporadic cases or small clusters of disease in people, but has not resulted in human-to-human transmission sufficient to sustain community-level outbreaks.
4	Human-to-human transmission (H2H) of an animal or human-animal influenza reassortant virus able to sustain community-level outbreaks has been verified.	Rapid containment.	Readiness for pandemic response.
5	The same identified virus has caused sustained community level outbreaks in two or more countries in one WHO region.	Pandemic response: each country to implement actions as called for in their national plans.	Readiness for imminent response.
6	In addition to the criteria defined in Phase 5, the same virus has caused sustained community level outbreaks in at least one other country in another WHO region.
Post-peak	Levels of pandemic influenza in most countries with adequate surveillance have dropped below peak levels.	Evaluation of response; recovery; preparation for possible secon
Posssible new wave	Level of pandemic influenza activity in most countries with adequate surveillance rising again.	Response
Post-pandemic	Levels of influenza activity have returned to the levels seen for seasonal influenza in most countries with adequate surveillance.	Evaluation of response; revision of plans; recovery

Source: WHO (2009)Table 3.

On the one hand, it is widely recognized that social capital itself has played a key role during the crisis. On the other hand, the importance of the interaction between social capital and other factors, such as education, age, and socioeconomic status (SES), has been investigated (Frankenberg et al., 2013). Some studies state that low SES results in a low level of social capital, while others have argued that low SES may be compensated by a high level of social capital (Ye & Aldrich, 2019). According to the ILO, 2.7 billion workers worldwide are affected by full or partial lockdown measures. Lockdown causes a drastic reduction in working hours, wage cuts, and layoffs or closes the market for agricultural products. The majority of the affected rural formal and informal workers are without access to healthcare and social protection, particularly in the low- and middle-income groups in India. According to Uphoff et al. (2013), people with lower socioeconomic status generally have lower levels of social capital, and that lack of social capital is related to socioeconomic inequalities in health. Main actions in affected and nonaffected countries have lower levels of social capital, and the lack of social capital is related to socioeconomic inequalities in health. Subramanian et al. (2002) show the adverse effects of linking social capital for individuals with low economic capital.

Considering these previous findings, the purpose of this article is to explore five significant aspects regarding the extent to which the social capital base affects (i) trust within the community, (ii) the preexisting rules before the disaster, (iii) the number of people who help those who are not immediate household members in life crises, (iv) how people learn about new community rules, and (v) communication between government officials and caste-based leadership, which supports recovery from the COVID-19 crisis.

This paper is organized as follows: section 2 reviews the related literature and the time of uncertainty; section 3 explains the research method and background; section 4 presents the data analysis; and section 5 discusses the conclusions.

2. Review of the literature

2.1. Social capital in the time of COVID-19

In every century, humankind faces uncertainty together, and social capital is the collective value of relationships. According to Panday et al. (2021), social capital revolves around social relationships and how individuals and communities utilize them in accessing emotional, financial, and physical resources and fulfilling their recovery and survival needs during times of uncertainty. Social capital is a central aspect of human civilization, particularly in times of disasters. One of the most recent disasters in the history of humankind is the COVID-19 pandemic, which has had profound and far-reaching disruptive effects. The disruption caused by the COVID-19 pandemic varies by industry and location. However, one common aspect has been the challenge and the opportunity to stay socially connected. The pandemic has revealed the importance of what humanity entails and affirmed that we are all connected somehow, and relationships matter.

The COVID-19 pandemic has been a major challenge worldwide. The world is facing a new challenge regarding leadership in uncertainty, as the COVID-19 crisis is the worst challenge leaders have faced in the last decade. The crisis was unexpected and unprecedented, and it forced the world to react in different ways. It can be argued that COVID-19 has shown the world that leadership is a skill that can be learned. It is not a skill that can be acquired overnight. Leadership is a process, and it takes time to build leadership capability (Cruz-Torres et al., 2021). It is necessary to be prepared for any crisis, such as COVID-19, which requires leadership, planning and prioritizing and preparedness to react quickly and in a timely manner. The challenge is to build leadership capability in the face of uncertainty. The world is in a state of uncertainty, and therefore, leadership is critical. The leadership crisis is real. The virus will continue to impact countries around the world. Different societies have different priorities, and the actions that are taken are based on these priorities. In this context, leadership is very relevant, and national leaders have different qualities, which affect their actions and the actions of their countries.

Leaders are people with different skills, motivations, styles, knowledge, and experience, and they take different actions based on their priorities. Likewise, nations respond to different challenges in diverse ways based on their priorities (Kokubun & Yamakawa, 2021). The unprecedented COVID-19 pandemic is one such challenge. The world is a global village, and the leadership crisis will continue. The crisis is global, and the different nations affected have had different responses to the crisis.

We focus on three concepts of leadership: positive leadership, deontological theory, and moral and ethical frameworks. Positive leadership is a leadership style that involves using a positive attitude and a sense of purpose to inspire others to follow. It is a style most often associated with leaders who are considered inspirational and have a strong sense of mission and purpose. In this paper, we examine the role of leadership in the economy during the COVID-19 pandemic. As the economy and economy-related sectors come under more pressure, the need for leadership skills increases. The challenge is to identify and support leaders amid these challenges.

Leadership is a complex and multifaceted concept. It can be described as a set of skills, behaviors, and attributes that support an individual or a group to successfully achieve a shared purpose. The concept of leadership has been studied for many decades and is recognized as a complex concept. Leadership includes a variety of skills and behaviors that are required for a leader to lead others. From a practical perspective, leadership concerns an individual’s ability to influence others to perform a task positively and cooperatively. Leadership can be defined as “the capacity for making decisions and taking actions that are in the best interests of the organization”. It involves the ability and willingness to take proactive steps to enable the organization to move forward efficiently. It also implies the ability of the organization or its subunits to create an environment characterized by unity, collective effort, cooperation, and a sense that the organization is working toward a common goal. Leadership also implies that the leader is willing to accept criticism and bear responsibility.

The interaction of positive leadership and trust is also important, especially in times of uncertainty. Individuals who cannot act based on their own judgment during the pandemic tend to rely on trusted leaders or officials to respond to the crisis. In other words, leaders need to have positive leadership and trust to cooperate with individuals in the community (Ahern & Loh, 2020; Siegrist & Zing, 2014).

COVID-induced uncertainty has been a major challenge for leaders who support deontological theory. In the social sciences, deontological theory is a meta-analytic approach that uses game theory to study the decision processes of individuals. The main relevance of this theory in the context of uncertainty is that it provides a framework for understanding individuals' decision-making in the face of uncertainty. It has a range of applications to real-life situations of uncertainty and has been used to support decision-making in public health (Lee et al., 2021) and to explain individuals' behavior in the presence of uncertainty during crises and disasters, including the current pandemic. This study applies deontological theory and the analytical framework it provides to the COVID-19 pandemic to understand individuals’ decision processes and behaviors in the face of uncertainty.

COVID-19 has led to unprecedented difficulties worldwide. In particular, the pandemic has led the world to a new era of uncertainty. The COVID-19 crisis is a global phenomenon to which the world must adapt. In this respect, the World Health Organization (WHO) has provided an appropriate framework to help countries address this uncertain reality. The WHO defines the crisis as a public health emergency of international concern (Panday et al., 2021), as it entails the worldwide spread of a disease that constitutes a risk to the health of people in the affected countries and cannot be contained, despite the best efforts of the affected countries.

In this context, the WHO has defined the framework for the crisis in the form of a set of principles and guidelines. These recommendations are based on the principle of solidarity, which states that all countries should work together to face the crisis, and no country should be left behind to deal with needs and challenges on its own. Each country affected by the crisis should take the necessary measures to protect its population. Each country should also take responsibility and cooperate to address the consequences of the disease for the affected population (Panday et al., 2021). The affected and vulnerable populations in the different affected countries should all be protected at the same time to prevent the pandemic from spreading from one country to another. Such cooperation is the only way to prevent the pandemic from spreading across countries.

To contain the outbreak within countries with infections, the affected countries should take appropriate measures. Based on expert analysis of the situation, the WHO has defined guidelines for the management of the pandemic crisis. This framework was designed to provide the necessary tools for countries to manage the pandemic. The guidelines are targeted to the different stages of the management process, including the initial stage of preparation, which should give countries time to prepare for the pandemic and to prevent the spread of the virus.

3. Data and method

3.1. Participants and procedure

The first step in this study was data collection and analysis in Jalna, a district in the Aurangabad division in Maharashtra, which has been facing a high level of confirmed cases of COVID-19 (Fig. 1 ). To draw Fig. 1, official statistics are collected from the government of India. Primary source data were collected through questionnaire surveys and interviews with key stakeholders who either experienced COVID-19 personally or lived with family members who did. Secondary source data were collected from official records, previous studies, books, publications, journal articles, reports, and local newspaper articles about rehabilitation efforts in the affected areas. Individuals who had first-hand experience with COVID-19 or who lost a family member in the pandemic period were the main subjects with the aim of analyzing how social capital affected (a) individuals with no personal experience of COVID-19, (b) individuals who tested positive for COVID-19, or individuals who lived with a family member who tested positive. We selected these two groups from six villages in Jalna District (Fig. 2 ). A list of positive patients was collected from a primary health care medical officer. We interviewed people in each village who experienced COVID-19 in 2021, followed all government rules of isolation and had medical check-ups on a regular basis. We asked local college students and other educated people of the selected villages to conduct the interviews. We visited 378 households in total (Map 2); 230 of the residents refused to cooperate or were unable to answer. The study explored how social capital and leadership affected people from groups a and b. The interviewees indicated their views about government policy toward COVID-19 victims. We also asked whether they believed that the central and state governments played a more active role during the period and whether they believed that social capital and community leadership helped with the recovery. We analyzed these factors using a Cox proportional hazards (CPH) model.

Fig. 1.

(Map of India)

Note: The figure illustrates the confirmed case of COVID-19. The unit of value is one hundred thousand cases. The value ranges from zero (0, white) to all (70, dark shaded). States with darker shades have a higher number of confirmed COVID-19 cases. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Source: The government of India, figure drawn by the authors (accessed on 21 September 2021).

Fig. 2.

Map of Jalna.

Source: the Gazeteer of India, Maharashtra State, Aurangabad District.

In Maharashtra, the social and economic development pattern varies throughout the state, and there are mismatches in the level of public services and basic facilities provided by the government. Jalna District is approximately situated at the center of Maharashtra state of the Republic of India; therefore, the GOI has established a satellite monitoring station near Jalna city for communicating with other satellites in space. In total, there are eight districts under the Aurangabad division, and Jalna is one of the least developed. The geographical area of the district is 7687 sq. km, covering 2.15% of the state. According to the 2011 census report, the district covers 958 villages with an average of 2045 people per village, yielding a total population of 19,58,483. In total, 80.73% of the area is categorized as rural and 19.27% as urban, and 71% of the total population is involved in agriculture or agriculture-related activities. The literacy rate in Jalna district is very low, 69%, compared to the state literacy rate of 82.34% for the same period. Regarding health facilities (2017–2018), there were 11 government- and public-aided hospitals and 40 dispensaries. This translates into approximately 272 beds per 100,000 people, one hospital in the city area, and one dispensary for every 40,000 people in the rural area.

3.2. Data analysis

Information on infection status and social capital was collected by a survey in Jalna and used for econometric analysis. In this section, we quantify the impact of social capital on the likelihood of COVID-19 infection. First, the section explains the econometric specification and variables that are used in the empirical analysis. Second, the results from estimations are summarized, and we discuss the relationship between social capital and COVID-19 infection.

To quantify the effects of social capital on the infection probability of COVID-19, we considered both survival duration and COVID-19 infection events using an event history analysis. We defined COVID-19 infection as a positive reaction of the respondent or family members to COVID-19. To conduct CPH analysis, as developed by Cox (1972), we construct a pseudo dataset in which all respondents and their family members present a negative reaction to COVID-19 at t-1, as our original dataset is based on cross-sectional data (Fig. 3 ).

Fig. 3.

Image of datasets.

CPH analysis has been widely employed by medical and other related studies to explore causality, e.g., the efficacy of a drug, health problems caused by smoking, etc. In this study, we also use CPH analysis to identify the causal relationship between social capital and the COVID-19 infection rate.

The specification of the econometric analysis is as follows:

$$h_i\left(t\right)=h_0\left(t\right)\exp \left({\beta }_1{x}_{i1}+{\beta }_2{x}_{i2}\dots +{\beta }_k{x}_{ik}\right)$$

where i represents the respondent. $h_i\left(t\right)$ is the dependent variable expressing the hazard rate for i to be infected at time t, and $h_0\left(t\right)$ is the baseline hazard function. The baseline hazard is presented as the result when all covariates are zero. The hazard ratio is higher than one, which indicates that the variable is highly likely to have a positive relationship with the hazard rate, and vice versa. $x_i$ and $\beta$ represent the individual variant independent variable and estimated coefficients, respectively. Regarding the form of the hazard function, the CPH model does not have any specific assumptions.

The dependent variable is the hazard of COVID-19 infection of the respondent or his or her family members, and it equals 1 if the respondent or his or her family members were infected and 0 otherwise. For the independent variables ($x_i$), as we focus on trust and communication as social capital, we employ the variables listed in Table 2. For all variables except “participation in community activities”, a higher value means a higher level of social capital. According to the ${\chi }^2$ test, only “participation in community activities” may differ among respondents. Nevertheless, this does not mean that there is no connection between other independent variables and COVID-19 infection. To check the relationship between them, the econometric results are summarized in the next subsection.

Table 2.

Type of variables and descriptive statistics.

Type of social capital	Name of variable	Question	Answers	χ2 Statics (p-value)	Mean	Median	SD
Trust	Trust among community(a)	Regarding information about Corona, which people among the following would your trust the most? (a = first, b = second, c = third)	6: Village head 5: Neighbours 4: Religious community 3: Relatives 2: Son or daughter 1: Hasband or wife	3.64 (0.602)	2.60	2	1.31
	Trust among community(b)			3.46 (0.628)	4.01	4	1.31
	Trust among community(c)			5.98 (0.308)	4.86	5	1.06
	Participate in community activities	How likely is it that people who do not participate in community activities will be criticized or sanctioned?	1: Unlikely 0: Likely	2.75 (0.097)∗	0.29	0	0.45
	Number of people help in life crisis	If you suddenly faced a long-term emergency, such as death of a breadwinner or harvest failure, job loss, how many people beyond your immediate household could you turn to who would be willing to assist you?	4: Five or more 3: Three or four 2: One or two 1: No one	4.37 (0.224)	3.23	3.5	0.93
Communication	Source to know new community rules	How do you know the new rules or regulations taken at village level by leaders?	3: Local community 2: Family member or relatives 1: Newspaper 0: Do not know about new rules	5.20 (0.157)	1.81	2	1.19
	Communication with the local government	In the past 12 months have you personally had contact with an elected local government official leader on a matter of concern to you?	4: Many times 3: A few times 2: Rarely 1: Never	1.95 (0.581)	1.49	1	0.82
	Communication with the caste-based leader	In the past 12 months have you personally had contact with older caste-based leaders on a matter of concern to you?	4: Many times 3: A few times 2: Rarely 1: Never	6.41 (0.093)∗	1.65	1	0.90

Note: + indicates that the results are statistically significant at the 10% level.

^∗10% statistically significant.

4. Results

In this subsection, the connection between social capital and infection probability is discussed according to the econometric results. The results are reported in Table 3.

Table 3.

Estimation results of the Cox proportional hazard model.

Independent variables	(1)	(2)
Trust among community(a)	0.978
	(0.0399)
Trust among community(b)	0.947
	(0.0421)
Trust among community(c)	0.949
	(0.0503)
Participate in community activities	1.180	1.211+
	(0.135)	(0.136)
Number of people help in life crisis	0.941	0.933
	(0.0533)	(0.0528)
Source to know new community rules	0.916+	0.925+
	(0.0434)	(0.0438)
Communication with the local government	1.092	1.106
	(0.0948)	(0.0929)
Communication with the caste-based leader	0.853+	0.856+
	(0.0772)	(0.0717)
Number of subjects	148	149
Number of Failure	98	99
Time at risk	148	149
Number of observations	148	149
Log pseudolikelihood	−487.172	−493.277

Robust seeform in parentheses.

**p < 0.01, *p < 0.05, + p < 0.1.

First, neither the order of people most trusted within the community nor the number of people who help during the crisis seems to have an impact on the likelihood of COVID-19 infection. The reason for the result could be the homogeneity of the responses. The medians of “trust within the community (a), (b), and (c)” are 2, 4, and 5, respectively, which indicates that most individuals tend to trust their family members more than the religious community or village head. Notably, these results do not indicate a low level of trust in local communities.

Second, according to the results, if a person believes that people in the village need to participate in community activities, the infection probability of COVID-19 decreases by approximately 21%. This implies that a high level of social ties and networks might result in a decrease in the COVID-19 infection rate in the area. It also indicates that community-based rule construction and compliance in ordinary times matter for individuals’ behavior during times of uncertainty.

Third, the source of individuals’ knowledge of new local rules may matter for COVID-19 infection. Based on the results, for instance, if a respondent learns a new rule through the government-approved local community instead of family members, the infection probability decreases by 7.5%. This result suggests that a high level of communication with the local community might enable people to take action to reduce the risk of COVID-19 infection. In particular, the Gram Panchayat fn1 plays a critical role in India, and receiving information from them seems to be key for safety behavior during the pandemic.

Fourth, communication with caste-based leaders plays a vital role during the crisis, while communication with the local government might not have an impact on COVID-19 infection. The difference in the infection probability between “many times” and “a few times” is approximately 15%. The result might reflect the importance of leadership in uncertain times, although the analysis does not include variables that express the level of leadership.

Note: Robust standard errors are in parentheses for the Cox proportional hazard estimation. + indicates that the results are statistically significant at the 10% level. The dependent variable is the hazard of COVID-19 infection of the respondent or his or her family members, and it equals 1 if the respondent or his or her family was infected and 0 otherwise. For all variables except “participation in community activities”, a higher value means a high level of social capital.

5. Discussion

The implications from the results are twofold. First, the source of information on COVID-19 is one of the significant issues during the pandemic (Lee et al., 2021). In the questionnaire, a large proportion of people answered that the people they most trusted regarding COVID-19 information were their family members. This result implies that if family members trust rumors more than information from the government or Gran Panchayat, collecting knowledge and news about COVID-19 from family members may mislead the family. Furthermore, family members could misinterpret the information from the government or Gran Panchayat. Thus, the government must be trusted by the people of India so that citizens believe the notices from the government and accept official information. Additionally, notices from the government need to be easily understandable.

Second, participating in local activities in ordinary times is quite important (Liu & Wen, 2021). In India, there are three main campaigns: “Save the girl, child, educated girl child”, “Clean India, clean your village”, and “Catch the rain”. Additionally, each village has its own local activities, such as keeping water clean and protecting women. People who join these activities tend to act in their villages’ interests and face reduced COVID-19 infection risks during times of uncertainty. Therefore, creating an atmosphere that encourages villagers to participate actively in national and local activities in normal times is important to develop social ties among local people.

Overall, social capital, such as trust and communication, may affect safety behavior during times of uncertainty. Our research also found that when community members followed the rules of the community before the pandemic, villagers may follow state/national recovery policies more closely to recover their communities. Our research concluded that social capital is vital in response to natural or manmade calamities; however, whether a community successfully develops social capital that is absolutely based on trust and faith is strongly related to how the community works in normal life. The strength of social networks, bond among and commitment of residents to the community, positive leadership, and various social factors influence the future implementation of government policies.

6. Limitations

Future studies should gather information on the abilities of leaders to explore the importance of positive leadership precisely. Likewise, future studies should investigate under what conditions social capital and positive leadership work well in times of uncertainty.

The paper also had several strengths, including the unique individual-level dataset and multiple variables regarding social capital, which allowed the paper to quantify the effect of social capital on COVID-19 infection.

7. Conclusion

This paper investigates the impact of social capital on COVID-19 infection by collecting information on villagers in Jalna, India, and by conducting econometric analyses. It concludes that individuals with a high level of social capital helped reduce or control other community members for recreational and other periodical social activities when maintaining social distance was not practical. Additionally, positive leadership and various social factors influence the future implementation of government policies.

Authors’ contributions

A. Joshi helped design the study and create the study questionnaire. S. Haneda conducted the data analyses. All authors participated in the interpretation of the results. All authors prepared the original draft of the manuscript. All authors participated in the reviewing and editing of the manuscript. All authors read and approved the final manuscript.

Funding

This research did not receive any specific grants from funding agencies.in the public, commercial, or nonprofit sectors.

Availability of data and materials

The datasets generated and/or analyzed during the current study are not publicly available. However, they are available from the corresponding author upon reasonable request.

CRediT authorship contribution statement

Abhay Joshi: conduct the actual survey in India Jalna to collect the raw data. Sho Haneda: play major role for analytical calculation. .

Declaration of competing interest

The authors declare that they have no competing interests.