Literacy and Response to COVID-19

Arijit Das and Soma Wadhwa ( are Fellows, and Tanya Bansal and Devutty Retnakaran are Research Assistants at the India Development Foundation.
19 August 2021

Demand for vaccination, as well as access to it, is uneven and sluggish across various parts of India. This article delves into the explanations for this variation from a demand perspective. We find a positive correlation between literacy and the first dose of vaccination. A similar trend is discernible for the demand for vaccines. Also, we find that higher literacy is associated with greater vaccine coverage among women. This nexus between literacy and health preparedness is further substantiated by our findings at the micro-level from an adult literacy evaluation study conducted in early 2021. About 80% of the literate women we surveyed were aware of the COVID-19 symptoms, compared to only 19% surveyed illiterate women. We found that literate women are more likely to wear masks properly and follow COVID-19 protocols and keep abreast with the news and information about COVID-19. 

All Indian citizens above 18 years of age are now eligible for the COVID-19 vaccination. But the demand for vaccination, as well as the access to it, is uneven and sluggish across different regions of India (Sharma 2021; Choudhury 2021). Reasons for this patchy progress need to be investigated urgently if universal vaccination is to be achieved within a stipulated time limit. For now, such inquiries almost entirely comprise discussions on the roles of various types of literacies as enablers and impediments to an appropriate COVID-19 response—including vaccine literacy, health literacy and digital literacy.  Regrettably, however, such discussions fall short of drawing links between the response efficacy of different populations to COVID-19 and the most literal form of literacy, defined as the ability to read and write. 

The United Nations Educational, Scientific and Cultural Organization (UNESCO) had, in fact, as early as in May of 2020 declared that globally, the COVID-19 crisis had hit the marginalised the hardest, which included 773 million non-literate adults and young people, of whom two-thirds were women. As also 617 million children and adolescents who had been failing to acquire basic reading and numeracy skills even before the pandemic. In India, given its 287 million illiterate people (Census 2011), mapping the connection between illiteracy and the ravages of COVID-19 is critical to directing our policies towards containing the pandemic.

Pertinently, there is extant literature on the relation between literacy of populations and their observation of health protocols, as also their responses to health emergencies. Much before the pandemic, researchers have pointed out the positive correlation between health outcomes and literacy (Dewalt et al 2004). Individuals with lower literacy skills are known to often suffer from poor health. This is due to misinterpretation of health information, miscommunication with healthcare professionals, issues with following directions given with medicines, and much more (Berkman et al 2011). These obstacles can also lead to smaller medical problems turning into larger ones requiring longer recovery times. Jacobson et al (1999) finds limited or marginal literacy as the cause for lower immunisation against pneumonia among older populations in the United States.

In India, evidence from empirical research studies indicates that female literacy leads to improved health indicators in families. These include delayed age of marriage, fewer and healthier children, better antenatal care, improved vaccination and nutritional status of children, reduced infant and child mortality, and corresponding reduction in poverty (Alexander 2018).

Mapping Links between Vaccination Coverage and Literacy in India

The Government of India (GoI) has developed the CoWIN portal for booking, monitoring and keeping countrywide records of vaccinations. It is a single window platform for all of India’s vaccine related information. We have been scraping the CoWIN website and collating the data available on it at routine intervals. While doing so, we have identified the particular data gaps that limit a deeper understanding of the advancement of India’s vaccination process. Further, we have devised methods to fill these gaps with alternate datasets available to us, like the census, National Sample Survey and National Family Health Survey. 

In this article, we use vaccination data from 16 January 2021 to 20 July  2021 scraped from the CoWIN website. All other data used have been taken from the 2011 Census. Since it is 10 years old now, we make projections for 2021; we use the GoI’s Ministry of Health and Family Welfare projected population formula to do this. Further, we merged district level CoWIN information on vaccination with district wise demographic details available in the census. The resultant combined dataset provides us with information for 735 districts out of the current total 741 districts in India. All the parameters (that is, number of vaccines administered, registrations and female vaccinations) used in this article are normalised with populations of respective districts, so that these values that are measured on different scales are adjusted to a notionally common scale. Description of the data extracted from CoWIN and Census 2011 is given in Table 1. 

Table 1: Description of Data from the CoWIN Website and Census 2011 



Vaccine coverage

District-wise number of individuals vaccinated with at least the first dose; divided by the population of the respective district and expressed as a percentage. This data was collected till 20 July 2021.

Vaccine demand

District-wise number of individuals who registered for appointments for vaccination in the CoWIN website; divided by the population of the respective districts and expressed as a percentage. This data is available on the CoWIN website only till 31 March 2021.

Vaccine coverage among women

District-wise number of females vaccinated, with at least the first dose; divided by the total population of the respective district and expressed as a percentage. Total population is taken due to the unavailability of gender-disaggregated population data for over 100 districts formed since Census 2011. This data is available on the CoWIN website only till 24 June 2021.

Literacy rate

District-wise literacy rate as per Census 2011, which is the latest data available.

At the initial level, our investigation of the data shows that Kerala, Delhi and Gujarat were, till 20 July 2021, the best performing states in terms of vaccinating their populations with at least one COVID-19 vaccine dosage. While Bihar, Uttar Pradesh and Jharkhand lagged behind. These findings are in keeping with other reports that point out a similar pace in the vaccination process across different states (Achom 2021; Basu 2021). Subsequent to which, we delved further into the explanation for this variation from a demand perspective. 

Literacy and Vaccine Coverage

We find a high positive correlation between literacy and the first dose vaccination coverage (refer to Figure 1). Also, our econometric analysis shows that vaccination coverage is significantly dependent on literacy levels, even when we take availability of vaccination centres into consideration and control our calculations for this. This means that districts with high literacy rates are more likely to have high vaccination coverage. For example, the Pathanamthitta district of Kerala with a literacy rate of 97% has vaccinated 50% of its population. Whereas, the Nuh district of Haryana with literacy rate of 54% has been able to administer first doses to only 10% of its population.

Figure 1: Link between Literacy Rate and Vaccine Coverage

Literacy and Vaccine Demand 

Not just overall vaccine coverage, our analysis finds that even vaccine demand is positively correlated with literacy rate (refer to Figure 2). We arrive at this finding by using the proportion of people who registered for vaccination on the CoWIN website as a proxy for vaccine demand. Here too, and expectedly so, Kerala’s Pathanamthitta tops in vaccine demand and Nuh district of Haryana secures the last spot. 
Statewise result shows Gujarat with a 78% literacy rate topping the list with 6% of its population having registered for vaccination. Bihar with the country’s lowest literacy rate at 62%t, has only 2% of its population registering for vaccination on CoWIN. 
Figure 2: Link between Literacy Rate and Vaccine Demand

Vaccine Coverage among Women and Literacy 

The positive correlation between literacy and vaccine coverage extends to include greater vaccine coverage among women in regions with better literacy rates (refer to Figure 3). For instance, significantly higher participation by women in the ongoing vaccination drive is observed in Kerala where 1,206 women are getting vaccinated against 1,067 men on an average. Whereas vaccination of women is lowest in Uttar Pradesh, where 741 women are getting vaccinated against 1,000 men on an average. Literacy is higher in Kerala at 94% than in Uttar Pradesh at 68%. District-wise results show that 23% women have been vaccinated till 24 June 2021 in Pathanamthitta district of Kerala as opposed to Lakhimpur Kheri district of Uttar Pradesh where only 3% women have been administered the first dose. The literacy rates in Pathanamthitta and Lakhimpur Kheri are 97% and 61%, respectively.
Figure 3: Link between Literacy Rate and Vaccine Coverage Among Women

Study on Literacy and Response-readiness to COVID-19 

Our findings on the literacy-health response nexus at the countrywide level as mentioned above are further substantiated by the results of a study we conducted in early 2021. These results are part of the findings for an evaluation study of an adult literacy programme for women in the Aurai and Lalitpur districts of Uttar Pradesh and the Haridwar district of Uttarakhand. We surveyed 565 literate women who were participants in the adult literacy programme and able to read Class 1 level text. We also surveyed 285 illiterate women, unable to read, in similar locations for comparison. 

We used a two-stage cluster sampling method to select the literate women to be surveyed. Since the adult literacy programme was being implemented in 90 villages in three districts, we considered villages as clusters and stratified villages across these districts. This process ensured representation of all three districts in the survey. We ranked the villages on their initial female literacy situation (as per the 2011 Census) and divided them into tertiles. Three villages were chosen from each tertile, creating a pool of 27 treatment villages of literate women to be surveyed. In the second stage, after selecting the villages, we sampled literates (participants of the adult literacy programme) who were to be surveyed. Then, we randomly selected 25 women from each selected village.

To sample for the control group of illiterate women, we created a cohort of villages in the same districts. Then, using the propensity score matching (PSM) technique (a process to match treated and untreated subjects who share a similar value/score), the closest matches to intervention villages were identified. Villages were matched on demographic and economic characteristics, and also on access. We identified one control village against every treatment village. Thus, a total of 27 control villages were identified.  Then, households were randomly selected and a literacy test was administered to identify illiterate women. (Due to COVID-19 exigencies, however, we were forced to drop 12 control villages; the sample size of women in the control group was also affected).

Our survey was followed by focus group discussions and in-depth interviews in three surveyed villages, one from each programme district. This particular way of analysing information is known as sequential exploratory mixed methodology. Informed by Creswell (2013), this design is characterised by the collection and analysis of quantitative data in the first phase, followed by qualitative data collection in the second phase. The qualitative data collection in fact builds on the results of the quantitative round. Finally, both types of data are integrated to make for the study’s analysis and findings. The understanding of the analysis and findings is enriched by secondary and programme data. 

The survey questionnaire for the study consisted of 12 sets of questions on various topics, including: basic information about the respondent; feedback on programme; mobility; economic activity, access to information; and decision making in the household. This article draws from questions related to health, hygiene and COVID-19. Table 2 describes the survey data used for this article.

Table 2: Description of Survey Data from a 2021 Study of an Adult Literacy Programme for Women



Awareness of COVID-19 symptoms


  • Women were asked: “Are you aware of COVID-19 symptoms?’’

  • Respondents who answered in the affirmative were asked: “What are the symptoms of COVID-19?”  

Awareness of the correct way to wear a mask

  • Four images of people wearing masks were shown to respondents. Only one image portrayed the correct way of wearing a mask.  

Washing hands to prevent illness

  • Women were asked: “Can washing hands prevent your friends and family from illness?”


  • Women were asked: “Do you have access to a newspaper?”

  • Respondents who answered in the affirmative were asked: “Do you read a newspaper?”

news on TV

  • Women were asked: “Do you have access to a TV?” 

  • Respondents who answered in the affirmative were asked: “Do you watch the news on TV?”

Visiting hospital alone in the last six months 

  • Women were asked: “Have you visited the hospital because you were ill, or taken a sick family member to the hospital, in the last six months?”

  • Respondents who answered in the affirmative were asked: “Did you make the hospital visit for yourself, or with a sick relative, alone?”

The results of our survey showed literate women substantially ahead in managing the pandemic situation compared to their illiterate counterparts—even though they were not specially trained to do so because the programme’s teaching component had been completed before COVID-19 hit India. We found that the newly acquired literacy and numeracy skills of the programme participants has, in fact, enabled them to access information on health and use it effectively (refer to Figure 4).  

When asked whether they were aware of COVID-19 symptoms, about 82% of the literate women replied in the affirmative, compared to only 16% among the illiterate women. Importantly, the results reflected literate women as more equipped to follow pandemic protocols. Provided with four different illustrations on ways to wear a mask appropriately, 86% of the literate women were able to identify the correct option. Only 30% of illiterate women could do so.  
Further, the results showed that literate women are better aware of the importance of maintaining hygiene at home and more likely to follow appropriate medical protocols. More than 99% of the programme participants acknowledged learning about hygiene in their classes. At 100%, everyone among the literate group was aware that washing hands prevents illness. This number in the control group was 82%.

Our qualitative research investigated the causal factors affecting the survey results. Programme participants who were focus group discussants said that they were better prepared to deal with the pandemic because the ability to read had enabled them to keep abreast with news and information about COVID-19. This, they argued, had helped them be better prepared with prevention methods. In-depth interviews with family members of participants corroborated this. Their newly literate mothers and wives, observed daughters and spouses of programme participants, had now discovered a newfound interest in reading newspapers, and in turn watching news on television. This is in fact reflected in the survey results which show a substantive 98% of literate women who have access to a newspaper read it, and 83% of literate women who have access to a television watch news on it. Women said that this helped them access and absorb information related to the lockdown, also on the financial and health benefits extended by the government during the pandemic.

Figure 4: Response to COVID-19


Women who participated in the programme said they have started to source and understand information by themselves through newspapers and television news. They observed that they had understood the gravity of COVID-19 early on because they now consume news routinely. Further, women spoke of their newly acquired literacy and numeracy skills enabling them to negotiate their way in the outside world, including health centres and hospitals. Women said being able to read signages and ward numbers had given them this confidence and capability and freed them from being reliant on others to do so. In the survey, about 62% of the participants said they are now able to visit hospitals independently and have done so within six months before taking the survey. Only 13% of women in the control villages said they had done the same.


The COVID-19 pandemic is not going away soon and may even return in more distressing and disruptive versions in the future. To combat these possibilities effectively, we must use our immediate learning for future readiness. Keeping in mind India’s large volume of illiterate population, we should recognise the vulnerability of this population in combating a pandemic. We should acknowledge the unpreparedness arising from a very basic form of illiteracy, and devise strategies to correct this condition. 

In the past, India has implemented a number of adult literacy programmes with limited success. The National Adult Education Programme (NAEP) was launched in 1978. Forty-three years later, and despite other programmes since launched—such as the Rural Functional Literacy Programme (RFLP), National Literacy Mission (NLM), Saakshar Bharat Abhiyan, etc—India still has over 287 million adult illiterates. Now, with emerging technologies, adult literacy can be more effective and at the same time much cheaper to deliver. Our experience points at a solution that adopts a hybrid model for adult literacy programmes that combines computer-based learning and student-teacher interaction. With more adults functionally literate, India will be significantly more resilient against pandemics and pandemic-like situations.

The authors express sincere gratitude to the referee. The referee’s comments and recommendations have guided us greatly in adding to the relevance of our article.

Arijit Das and Soma Wadhwa ( are Fellows, and Tanya Bansal and Devutty Retnakaran are Research Assistants at the India Development Foundation.
19 August 2021