key: cord-0973830-ue8wv0e7
authors: Rubina, Mulchandani; Babu, Giridhara R; Avinash, Kaur; Ranjana, Singh; Tanica, Lyngdoh
title: Factors associated with differential Covid-19 mortality rates in the SEAR nations: a narrative review
date: 2022-02-27
journal: IJID Regions
DOI: 10.1016/j.ijregi.2022.02.010
sha: 9b903fb2fbc18a3b9a60d4f8f9faea61d8611889
doc_id: 973830
cord_uid: ue8wv0e7

Objectives : Since December 2019, the world has been grappling with the Covid-19 pandemic that has caused severe loss of lives, breakdown of health infrastructure and disruption of the global economy. There is growing evidence on mortality patterns in high-income countries. Still, similar evidence from low-middle-income nations is lacking. Our review aimed to describe Covid-19 mortality patterns in the WHO-SEAR nations and explore factors to explain such trends. Methods : A systematic and comprehensive search was undertaken in PubMed and google scholar to obtain maximum hits on Covid-19 mortality and its determinants in the SEAR using a combination of MeSH terms and Boolean operators. The data was narratively synthesized in detail under appropriate themes. Results : Our search identified 6411 unique records. Mortality patterns were described in light of important demographical and epidemiological indicators. Gaps in available evidence and paucity of adequate research in this area were also highlighted. Conclusions : This review discussed significant contributors to the Covid-19 deaths across SEAR nations, while emphasizing issues related to insufficient studies, data quality and reporting challenges and other concerns in resource-constrained settings. There is a compelling need for more work in this area to help inform decision making and improve public health response.

Since the first reported coronavirus disease case in China on December 31, 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused severe social and economic disruptions incalculable health and human toll worldwide. The effects of Covid-19 have been both direct in terms of infections and fatalities and indirect through imposing on constrained health systems across the world, including developed countries. Further, subsequent waves of the pandemic are currently underway across most countries globally.

Based on the evidence, Covid-19 mortality has exhibited a wide range of variability across different nations. A surprising reflection observed is that disease prevalence and the case fatality of Covid-19 shows a higher trend in the high-income countries as compared to low and low-middle income countries even though high-income countries have the higher gross domestic product (GDP) and improved Human Development Index (HDI) with better access to access to healthcare facilities, hygiene and sanitation.

While multiple factors can contribute to the outcome, the current paper attempted to explore reasons that explain these differential patterns across countries. Thus, we utilized the opportunity to describe Covid-19 mortality across the 11 countries (including Bangladesh, Bhutan, Democratic People's Republic of Korea, India, Indonesia, Maldives, Myanmar, Nepal, Sri Lanka, Thailand, Timor-Leste) in the South-East Asia region and identify factors (like population demographics, population health, epidemiology of the disease, and role of COVID appropriate measures) that may account for any observed differentials in the mortality rates.

We aimed to estimate the factors related to the differential nature of mortality associated with Covid-19 patients in countries of the Southeast Asian Region.

A systematic search was undertaken in MEDLINE via PubMed and Google Scholar from January 2020 to June 2021, using combinations of search terms joined by Boolean operators (AND; OR) as applicable. An initial search was conducted to curate a list of suitable keywords corresponding to the novel coronavirus or Covid-19 and the associated explanatory variables related to Covid-19 mortality such as epidemiological features, disease severity, underlying comorbidities and public health interventions. Corresponding MeSH terms were utilized to build a more comprehensive keyword library. A complete search string was created for each major explanatory variable and mortality as the outcome (joined by measures of public health interventions. Information was then summarized under appropriate themes that have been comprehensively described in the next section.

Our search identified a total of 6411 unique records. The number of studies identified in the search was highest for India, followed by Indonesia, Bangladesh, Nepal and Thailand, with very small numbers from the rest. Relevant published literature was almost negligible for a majority of countries.

After excluding preprints and non-peer-reviewed papers, a total of 5352 articles were screened by title and 1106 by abstract. Following this, full-texts of 465 articles were assessed for eligibility. A total of 106 studies were finally included in the narrative synthesis, with most papers from India, followed by Bangladesh and Indonesia, and a very small number of papers from Nepal and Thailand. Common reasons for excluding studies and the selection process is shown in the PRISMA diagram (Supplementary File S1). Table 1 shows the country-wise distribution of overall studies identified and screened.

In the following sections, we have summarized the mortality estimates across studies and explored the major epidemiological indicators that could play a role in explaining the Covid-19 associated deaths across the SEARO countries. Findings are reported for 5 out of the 11 countries (Bangladesh, India, Indonesia, Nepal and Thailand) in the South-East Asia region due to a paucity of data from the others.

The case fatality rates (CFRs) measured across the included studies from various SEAR countries varied from 1-5% to more than 30%. Of the total studies reporting data on Covid-19 associated mortality in Bangladesh, almost 63% reported a CFR of 10% or less. In India, the proportion of studies reporting a CFR of less than 10% was lower (about 53%). Approximately 37% of Indian studies reported a CFR of 11-25%, while the corresponding proportion of Bangladeshi studies was 25%. The data from other countries were largely inadequate for comparisons.

The CFR in Bangladesh ranged from 4-25% across most of the included studies (I. Hossain et al., 2020e, , 2020c Mowla et al., 2020 ; National Institute of Preventive and Social Medicine (NIPSOM), Dhaka, Bangladesh and Mph, 2020; Saha et al., 2020) . In contrast, two studies reported higher mortality rates, i.e. 57% and 77% (I. Hossain et al., 2020b; Saha et al., 2021) . The Dhaka region reported a significant proportion of all deaths (I. Hossain et al., 2020c; Mamun et al., 2020) . For India, the CFR ranged widely from 1% to 30% in most studies Borah et al., 2021; de Souza et al., 2021; Ghoshal et al., 2020; Jain et al., 2020; Mahajan et al., 2020b; Malhotra et al., 2021; Mathew et al., 2021; Mazumder et al., 2020; Mehta et al., 2021; Mishra et al., 2020; Mohan et al., 2020; Mohandas et al., 2021; Pujari et al., 2021; Soni et al., 2020; Tambe et al., 2020) , with the rates being somewhat higher (30-50%) in two studies with largely critical patients who succumbed to the disease (C. Singh et al., 2021; Suresh et al., 2021) . A very few studies from Indonesia reported mortality data, with the CFR being 7% and 10% in two studies Sutiningsih et al., 2021b) and one study conducted among elderly Covid-19 patients reporting a death rate of 23% (Azwar et al., 2020) . Similarly, only two studies reported mortality data from Nepal, with CFR being 11% and 45%, respectively Sherpa et al., 2021) . A single retrospective crosssectional study of confirmed Covid-19 cases from Thailand reported the proportion of deaths as 2.1% . Table 2 describes the characteristics of included studies reporting CFRs for the  SEAR  nations.  Their  current  community  CFRs  are  shown  in  Table  3 (source: https://coronavirus.jhu.edu/data/mortality).

Some of the major determinants of coronavirus disease-related deaths commonly reported across studies have been described below.

Older age and being a male were significantly associated with mortality in confirmed SARS-CoV2 cases across all hospital-based studies available from SEAR countries (Table 4) .

Disease severity was positively correlated with worsened prognosis and a greater likelihood of death. Among the SEAR nations, India reported the highest proportion of patients with severe Covid-19, followed by Bangladesh and Indonesia. Similar data from Nepal and Thailand was scarce (Table 5) .

The presence of multiple comorbidities, especially diabetes and cardiovascular conditions, had a strong significant association with infection severity, ICU support and fatality (Table 6) .

We also summarized the most common presenting symptoms among the hospitalized Covid-19 patients, as reported in the available literature (Table 7) .

We reviewed a few Knowledge, Attitudes and Practices (KAP) studies conducted in some SEAR countries that provided information on the general population's adoption of public health practices and adherence to the pandemic protocol. Data on wearing masks, maintaining hygiene and physical distancing behavior has been summarized in Table 8 .

The coronavirus pandemic that began over a year and a half ago in December 2019 continues to spread globally, claiming millions of lives due to the high transmissibility of SARS-CoV2 and its ability to mutate with time rapidly. The Covid-19 disease mortality has thus become a major cause for concern, especially with countries grappling with multiple waves that have crippled the health systems and caused massive human and economic losses. It becomes imperative to explore reasons for the differential mortality patterns observed across nations. In this paper, we attempted to explore a few factors that may account for these differences in death rates in the countries of the WHO-South-East Asia Region.

During March-July 2020, India reported the highest deaths per million, followed by Indonesia and Bangladesh. Nepal reported low numbers, and Thailand reported none. Over the second half of 2020, Indonesia and Nepal showed increasing numbers while India and Bangladesh fared better. There was a huge spike in mortality in India and Nepal during the deadly second wave in April-May 2021. By mid-2021, the situation improved across countries. However, Nepal and India continued to report higher estimates than the others (Figure 1 ).

CFRs reported across most studies included in this review were much higher than the national averages for the countries. This could be because most of the available literature reporting CFRs in the SEAR nations was from hospital-based studies. Small sample sizes and greater severity could substantially overestimate the actual mortality rates since more serious cases tend to be hospitalized. Communitybased studies, although very few, reported lower CFRs (Table 2) . 

Based on the available data, it was observed that although the proportion of severe covid patients ranged widely across studies, Bangladesh and Indonesia reported a somewhat lower percentage of severe and critical cases. In comparison, the percentage was higher for India. A consistent finding across all studies was the strong association of older age and diabetes and other chronic conditions with indicators of disease severity and mortality (longer hospital stay, ICU admissions, ventilator support). The greater predisposition of the elderly and those with comorbid conditions to severe Covid-19 has been well established in the literature ("COVID-19 High risk groups," n.d.; Sanyaolu et al., 2020; Verity et al., 2020) .

On exploring the presence of underlying comorbidities in studies included in the review, we found a high prevalence of diabetes and hypertension in Covid-19 patients across studies from all five countries (India, Bangladesh, Nepal, Indonesia, and Thailand). Cardiovascular disease, respiratory disorders, renal dysfunction, and cerebrovascular disease were also quite common. Interestingly, severe and critical patients were more likely to have multiple comorbidities (3 or more) or have diabetes accompanied by other illnesses like hypertension and heart disease.

The prevalence of adult diabetes in India is 8.9%, the second-highest globally. Also, according to the International Diabetes Federation, out of the 463 million people with diabetes worldwide, 88 million are in the South-East Asia Region (77 million out of which are Indians) ("IDF_Diabetes Atlas," n.d.). The high burden of NCDs in India and Nepal might have contributed to higher mortality in these countries. Noncommunicable diseases cause 60% of the overall mortality in India, out of which almost 26% can be attributed to cardiovascular diseases (CVDs) ("WHF_Cardiovascular Diseases in India Factsheet," n.d.). The prevalence of hypertension, a major risk factor for heart disease and stroke, is about 30% in India (Anchala et al., 2014) . Nepal also has an alarmingly increasing burden of NCDs. NCD prevention and control in the country has been one of the WHO Key Priorities in the SEA region since 2014 ("Persistent high prevalence of non-communicable diseases risk factors in Nepal," n.d.).

Regarding the common clinical symptoms of the SARS-CoV2 infection, studies showed that fever, cough, sore throat, and dyspnea were the most common presenting symptoms among infected patients. Dyspnea was more commonly reported in studies from Nepal and India. At the same time, cough was more common in Bangladesh, Indonesia, and Thailand, with fever being present across all countries. Dyspnea (shortness of breath) is considered one of the more severe symptoms of Covid-19. Evidence suggests that patients presenting with breathlessness are more likely to develop Acute Respiratory Distress Syndrome (ARDS) and have a poor prognosis ("COVID-19 basics," 2020; Wu et al., 2020) .

It is important to note the gaps in knowledge and awareness about Covid-19 highlighted in a few of these studies. Evidence from Indian studies suggests that understanding various aspects of the disease was suboptimal, including the importance of physical distancing, coughing and sneezing etiquette, transmission risk through asymptomatic individuals, person-to-person viral spread, and the role of respiratory droplets and the definition of high-risk groups. The survey respondents listed several barriers to adopting appropriate prevention practices against Covid-19. These included sharing a common room, using common fomites, overcrowding, space constraints, frequent hand washing being cumbersome and economic struggles. Studies from Nepal also showed limited awareness about covid appropriate protocol, misconceptions regarding quarantine, incorrect information on virus transmission through poultry and belief in non-scientific practices (using antibiotics, hairdryers, mouthwash, rinsing the nose with saline, and sesame oil and garlic being protective against infection) among the participants across multiple surveys. In eastern Nepal, there was a common belief that Nepalese were immune to SARS-CoV2, and this belief was even more common among rural Nepalese. Knowledge and awareness levels can be key drivers of behavioral change in the community (Kite et al., 2018) . Lacunae in communication and inadequate knowledge could contribute to the pandemic protocol violations, affecting public health outcomes.

Other variables could explain why certain countries had a better pandemic response than the others. Variations in mortality rates could result from differences in the number of confirmed cases and reported deaths due to varied testing strategies and counting approaches. Similarities or differences in implementation of Covid-19 guidelines like handwashing, physical distancing, wearing of masks, following lockdown/quarantine restrictions could also be a function of the type of government regimes across the nations, based on the level of control over the populations. It is possible that countries with democratic governments like Nepal and India found it more challenging to enforce preventive measures, in contrast to Thailand, which is a constitutional monarchy, or Bangladesh that has a government with an authoritarian bent (Sorci et al., 2020) .

Scientists worldwide have been debating about the disproportionately higher Covid-19 mortality burden in the high-income countries compared to the low and middle-income countries. Estimates from Johns Hopkins University and the WHO have shown that high-income countries account for almost 70% of the Covid-19 mortality. This phenomenon has perplexed researchers globally since one would expect the reverse due to superior health infrastructure and resources in developed nations. A few reasons that could explain this are younger populations in some of these LMICs (Supplementary File 2), warmer climate, lesser travel, and genetic and immunological differences in the profiles of Caucasians compared to other Ethnic groups (Vigo et al., 2020) . However, the situation is rather complex and involves other factors like data management, quality issues, and weaker surveillance systems in the LMICs, leading to a possible underreporting in numbers (Feyissa et al., 2021) .

SEAR nations have been facing various challenges regarding the estimation of Covid-19 associated mortality. Some of these include paucity of relevant data, lack of research, weak reporting systems for deaths such as verbal autopsies across these countries. This has led to a significant underreporting bias in the available numbers. (Desk, 2020 ; "Fears grow that Nepal's Covid-19 crisis could be even worse than India's," 2021; "Indonesia surpasses 100,000 deaths amid new virus wave," 2021; Team, 2021) . A few reasons recognized for undercounting of deaths and gaps in existing country-level data are insufficient hospital beds, oxygen supplies and other medical care in these regions due to an overwhelmingly high case load, especially during an infection surge, inconsistency in the definition of deaths from the coronavirus, inadequacies in reporting of age and sex-disaggregated data on Covid-19 mortality from the health ministry, unavailability of testing facilities and a high false-negative rate of rapid antigen tests Biswas et al., 2020; Hasibuan, n.d.;  "Number of Covid-19 deaths far higher than what the government claims, officials say," n.d.; Zimmermann et al., 2021) .

Epidemiologists and data scientists, along with journalists and volunteer groups, have been working tirelessly to access all possible sources and obtain credible data on Covid-19 mortality ("Estimating Covid-19 Fatalities in India," 2021; . This is to ensure that the numbers reflect the real picture of the infections, hospitalizations and deaths at any given point in time, and predictions regarding the future trajectory of the virus can appropriately inform and aid government policy. However, despite their relentless efforts, lacunae in health systems, frail surveillance mechanisms, and concerns with capturing and reporting of data have acted as hindrances to devising a more effective public health response.

Data paucity and quality issues are major problems in assessing the differential severity and mortality in Southeast Asian nations. While it is possible that real biological differences may explain the lower risk of severe Covid-19 in these nations, there may be alternative explanations such as differences in the quality of Covid-19 data and age structure of the populations. For example, people may be less likely to visit the hospital with Covid-19 due to stigma around the virus, or they may be more likely to die at home instead of in a medical facility. This means that the cause of death may be less well captured in these countries, and the true number of people with severe COVID-19 may be underestimated. To date, no study has fully answered whether the severity of Covid-19 truly differs in these nations.

To the best of our knowledge, this is the first narrative review that aims to describe the differential patterns of Covid-19 mortality among the WHO-SEAR countries and explores a few epidemiological indicators that could elucidate the differences. Our study has several strengths and a few limitations. We prepared a comprehensive and exhaustive search strategy to ensure a sensitive search that could fetch us as many relevant articles as possible. Additionally, efforts were made to elaborate on each indicator separately to present a thorough summary of the findings obtained from many studies.

However, the indicators included in this review could only partially explain the variations in mortality. Other variables like population density, health systems and medical infrastructure, economic status of the countries, and heterogeneity in estimating the number of deaths warrant further investigation. Moreover, the overall analysis is a narrative synthesis based on the available literature. Hence, the conclusions drawn cannot have causal inference. Also, relevant data from the remaining countries was insufficient or absent, due to which they had to be excluded from the summary. Even countries included in the review did not have enough data to establish associations between the explanatory variables and mortality outcomes. Lastly, published literature from community surveys on Covid-19 mortality in the SEAR nations was rather inadequate for comparison with data from hospital studies. In the light of these issues, the review findings warrant cautious interpretation.

Our review highlights important contributors to the burden of deaths associated with Covid-19 in SEAR nations. Resource constrained settings are more fragile and have thus taken a massive hit in LMICs than the developed world. Understanding factors associated with greater morbidity and mortality in developing countries to combat some of them is thus cardinal. This paper also calls attention to the scope for further research that could add to our knowledge on the various epidemiological and environmental indicators that can drive Covid-19 infection and death rates across countries. There is a compelling need for more studies in this area (especially community based), specifically from the SEAR and other low and middle-income countries.

The Covid-19 pandemic has exacerbated health inequities and exposed the fragility of the health systems, especially in the SEAR nations. Despite being adversely affected by the pandemic than the developed world, there is limited literature from the SEAR region. Conducting and publishing further research on Covid-19 associated mortality and its determinants can inform public health response. Details regarding caseload, morbidity and death rates can enhance our understanding of the actual scenario in the SEAR. This evidence base can drive better pandemic preparedness. In order to achieve this, impending issues related to data capturing, data quality and communication need to be addressed. Establishing a national health data repository for a robust and reactive surveillance platform that guides public health efforts is necessary for all SEAR nations. Strengthening disease control efforts, promoting research and stepping up medical infrastructure is essential. It can be accomplished by linking multiple platforms for data sharing while maintaining privacy and implementing digital health measures. It is also crucial to encourage community participation and leverage social engagement to strengthen the public health messaging approaches and inform the public. This would help these nations be better equipped to address health emergencies and tackle pandemics presently and in the future.

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

The study was conducted as part of the Technical Support Unit established at the Public Health Foundation of India for the World Health Organization to strengthen regional support in the technical analysis, inferences, and dissemination regarding Covid-19 response in SEAR.

Ethical approval was not required for this study. Mortality was reportedly higher in the older age groups, i.e. those who were 60 years and above. (Asirvatham et al., 2021; Gupta et al., 2020; Kumar et al., 2021; Mazumder et al., 2020; Mishra et al., 2020; Mohandas et al., 2021; Saurabh et al., 2021; Sharma et al., 2021; Older age was a risk factor for requiring intensive care too.

Being a male was found to be a greater risk factor for death. ) Asirvatham et al., 2021; Deshpande et al., 2020; Gaur et al., 2021; Kansara et al., 2021; Kumar et al., 2021; Mathew et al., 2021; Mehta et al., 2021; Mithal et al., 2021a; Mohandas et al., 2021; Saurabh et al., 2021; Sharma et al., 2021; Tambe et al., 2020 ) Indonesia Older age and being a male were strong predictors of mortality. Sutiningsih et al., 2021b Older age and being a male were strong predictors of mortality. Thailand Older age and being a male were strong predictors of mortality. The proportion of severe cases in Nepal was reported as 11% and 22% in the two eligible studies from the country, while most patients presented with mild or moderate symptoms. (Md, 2021; Sherpa et al., 2021) Thailand One study from Thailand reported 14% and 3% as the proportion of severe and critical cases of Covid-19. The prevalence of diabetes ranged from 20-65% among the majority of the studies, with two studies reporting a rather high prevalence of more than 90%. The prevalence of hypertension was also similar and ranged from about 15-60%. The prevalence of respiratory conditions had a narrow range, i.e. around 8-18%. Blood vessel disorders (cardiovascular and cerebrovascular diseases) ranged from 5-30%.

Patients with three or more comorbidities were more likely to present with severe/critical SARS-CoV2 symptoms than the others.

The proportions of people with diabetes (both insulin-dependent and non-insulin-dependent) and hypertensives were significantly higher in the severe group and among those requiring ICU care. Diabetes prevalence was also higher among older patients.

The prevalence of comorbidities was thus significantly higher among non-survivors, and there were more deaths in people with diabetes than non-diabetics.

(I. Hossain et al., 2020d; ) ; India In India, diabetes, hypertension, cardiovascular disease, lung disorders and renal disease were reported in a majority of the studies, with diabetes and hypertension being the most common. The prevalence of diabetes ranged from 15% to approximately 50-60% among the studies. Hypertension also had a similar prevalence ranging from 28% to more than 60%. The proportion of patients with heart and respiratory illnesses was lower, i.e. around 5-20%.

The presence of diabetes was accompanied by another chronic pre-existing condition like heart disease or hypertension in a few studies.

Diabetes and hypertension were more prevalent in the severe patient groups with a greater risk of fatal outcomes and those requiring oxygen and ICU support.

Male diabetics with Covid-19 constituted a highrisk group and were more prone to death as compared to others.

Hypertension was also found to be associated with severe cases of Covid-19.

using alcoholic rub for sanitizing purposes. Almost 1/4 th of the participants in a study reported handwashing practices and disinfection of items every time they came home as inconvenient due to lack of facilities, economic constraints and inadequate knowledge. India Frequent handwashing was adopted by more than 60% of the respondents in a community-based cross-sectional survey from India. However, washing hands for at least 20 seconds was not commonly observed, with less than half the respondents doing it. (Chakrawarty et al., 2020) Country Explanatory variable-Physical Distancing References Bangladesh The proportion of participants practicing physical distancing, avoiding crowds, meeting up with friends and eating out varied from 50% to 90%. An online cross-sectional survey on population-level preparedness for prevention against Covid-19 showed that a majority of the respondents found it inconvenient to live with older family members and practice distancing with members showing covid-like symptoms. 

The proportion of individuals reportedly maintaining physical distancing in public spaces and workplaces was about 50%, in a community based cross-sectional survey of 904 participants. Less than 20% had visited gyms, bars, restaurants and cultural gatherings. On the contrary, another cross-sectional survey among 452 adults reported almost 93% of the respondents practicing physical distancing. (Chakrawarty et al., 2020) ; (Kumar et al., n.d.) 

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Indonesia The comorbid conditions reported were hypertension, diabetes, cardiovascular disease

India Fever was the most prevalent symptom, followed by dyspnea. The prevalence of fever ranged from about 20-50% in some studies

2021) Indonesia Fever was the most prevalent symptom

2020) Thailand Fever was the most prevalent symptom, followed by cough

A hospital-based cross-sectional study from Southern Bangladesh reported that amongst the ICU patients, the proportion of those in the age group of 51-60 years was the highest (approximately 30%) compared to the younger age groups. Hasan et al., 2021; Paul et al., 2020; Saha et al., 2020 ) IndiaThe prevalence of severe symptoms among Covid-19 patients ranged from 3% to 50%.The percentage of critical symptoms ranged from 3% to 35%. (de Souza et al., 2021; Deshpande et al., 2020; Kayina et al., 2020; Kute et al., 2021; Mithal et al., 2021a; Mohan et al., 2020; Pujari et al., 2021; Saurabh et al., 2021; Soni et al., 2020; Suresh et al., 2021 ) Kayina et al., 2020; Soni et al., 2020) Indonesia The percentage of severe symptoms ranged from 7% to 40%. (Azwar et al., 2020; Surendra et al., 2021;  lung disease, and renal disease, with hypertension being the most common. The prevalence of hypertension ranged from about 20-40%, whereas diabetes was in a little more than 10% of the patients.The proportion of these pre-existing chronic conditions was higher among the deceased group. These illnesses were correlated with the development of the Acute Respiratory Distress Syndrome (ARDS). However, the number of studies reporting data on comorbidities was inadequate. Sutiningsih et al., 2021b) ; Rozaliyani et al., 2020; Surendra et al., 2021) ; Rozaliyani et al., 2020; Surendra et al., 2021) ; Rozaliyani et al., 2020; Surendra et al., 2021) ; Rozaliyani et al., 2020; Surendra et al., 2021 ) Rozaliyani et al., 2020) NepalThe most commonly reported comorbid conditions among Nepalese patients were hypertension, diabetes, cardiovascular disease, and lung disease.However, the number of studies reporting their prevalence was rather limited. One study showed a correlation between the presence of a chronic condition and Covid-19 mortality. Thailand Diabetes, hypertension and dyslipidemia had the highest prevalence among Covid-19 patients in Thailand. But prevalence data for these conditions was reported by less than a handful of the studies. Chailek et al., 2020; Pongpirul et al., 2020; Sirijatuphat et al., 2021) 

Bangladesh Fever was the most prevalent symptom, followed by cough. The proportion of patients presenting with fever was rather high, with around 60-90% prevalence across most studies. Cough was also seen in almost 2/3 rd of the patients. Dyspnea (shortness of breath) was prevalent in about 50% of the cases. Preventive practices adopted by the population were reported in just a handful of the studies. Almost 90% of the 904 participants in a community-based survey reported wearing masks. More than two-thirds of the respondents covered both their nose and mouth and avoided handshakes. (Chakrawarty et al., 2020) Indonesia The proportion of Indonesian respondents wearing masks was reportedly less than 75%. Almost 65% of the participants in a survey reportedly used cloth masks only, and just about 12% used both cloth and surgical masks for protection. (Kristina et al., 2020) ; (Pramana et al., 2020) Nepal According to a cross-sectional survey among 1069 residents of eastern Nepal, preventive measures were reportedly followed by almost 98% of the participants. A survey among 427 healthcare workers on perceived risk and the enabling environment in a medical setting showed that 10-20% of the staff did not always have access to face masks, soap and water, and hand sanitizers. (Chapagain et al., 2020) ; (Sarraf et al., 2020) Country Explanatory variable-Sanitation and Hygiene References Bangladesh The proportion of people reportedly washing hands frequently with soap and water was almost 90%. An almost similar proportion reported that they disinfected items that could be easily touched by many people, like surfaces and door handles. About 70% of the participants in a study reported cleaning and disinfecting their house regularly. Almost 94% used tissues for sneezing and coughing, then disposing of them in a waste bin. A small number of this study population supported