This study conducted among adults in nine LMIC from December 2020 to February 2021 showed that the COVID-19 testing uptake was 40.3% and that 7.3% tested SARS-CoV-2 positive, which is higher than in a large community survey in Canada (3.3% of those who had undergone testing were tested positive) [2] and in Germany (0.46 to 1.82% of the population-based cohort were tested positive) [5]. The high proportion of COVID-19 testing uptake and the higher proportion of positive SARS-CoV-2 tests may be partially attributed to the high participation rate of students or workers in the health care sector (34.4%) but also because in LMIC testing is more likely to be done among symptomatic individuals or persons in contact with positive cases.
Using the Andersen’s health care utilization model, we found that predisposing factors (residing in Brazil, postgraduate education), enabling/disabling factors (urban residence, higher perceived economic status, being a student or worker in the health care sector, and moderate or severe psychological distress), and need factors (having at least one chronic condition) increased the odds of COVID-19 testing. Previous studies also found that several underlying health conditions, higher household income, and occupation (health care worker) were associated with COVID-19 testing [2, 3]. Persons with underlying health conditions such as obesities, diabetes and cardiovascular diseases are at increased risk for developing severe diseases and therefore tested when they develop COVID-19 like symptoms [25]. People with higher education and higher economic status may have better access to health information, such as the importance of knowing one’s COVID-19 status. Unlike previous studies that found an association between older age, male sex, and uptake of COVID-19 testing [2, 3], we did not find age and sex differences in the uptake of COVID-19 testing. It is interesting to note the demographic differences in COVID-19 testing in LMICs, compared with previous studies conducted in Canada and the UK [2, 3]. Perhaps there was no concerted effort to test the elderly among the LMIC countries, unlike in Canada where long-term care facilities contributed significantly to COVID-19 mortality, necessitating the mass testing of elderly individuals [26]. Compared to Brazil, all other study countries had a lower uptake of COVID-19 testing. High COVID-19 testing was also observed among health care workers in Brazil (73.6%) [27]. This high uptake of testing in Brazil is explained by the high COVID-19 disease burden in Brazil and the widespread use of COVID-19 rapid antigen tests [28, 29].
Regarding the odds of COVID-19 positive diagnosis among all persons tested, residing in Bangladesh, and moderate to severe psychological distress were positively associated with COVID-19 positive diagnosis and residing in Malaysia and Thailand and higher education were negatively associated with a COVID-19 positive diagnosis. In the UK biobank data study, ethnicity (non-Whites) and lower education were associated with COVID-19 positive diagnosis [3]. However, both in this study and the UK biobank data study among tested persons, no significant association between comorbidities or health risk factors with a COVID-19 positive diagnosis was found [3].
The association between psychological distress and COVID-19 positive diagnosis has also been found among COVID-19 survivors in China [30] and may be attributed to stress reactions following the COVID-19 positive diagnosis potentially leading to long-term mental disorders [30]. In another study in China, depressive symptoms were more prevalent in COVID-19 patients compared to non-COVID-19 controls and were associated with an increase in inflammation markers [31]. Consequently, COVID-19 survivors should be screened for stress disorder, anxiety, and depression regularly to identify those with psychological distress for timely intervention [30]. The lower odds of COVID-19 positive diagnosis, among those with higher education can be explained by the significantly higher rate of COVID-19 testing among those with higher compared to those with lower education. Furthermore, it is possible that people with higher education and more access to quality information are more likely to take up vaccination, follow COVID-19 prevention measures and hence are less likely to become infected [32, 33]. The higher rate of COVID-19 positive diagnosis in Bangladesh may be explained by a higher prevalence of COVID-19 pandemic in Bangladesh (15.1%) [12], and the reluctance of people to get tested for COVID-19, when they have no or only moderate COVID-19 symptoms [34]. The lower rate of COVID-19 positive diagnosis in Malaysia may be attributed to a lower average test positive ratio and testing rate (4.3% and 0.8 tests per 1000 population) [11]. In Thailand the low rate of COVID-19 positive diagnosis may be attributed to a low prevalence of COVID-19 infection (7.5% among hospital patients) [13], and a low-test positive ratio (1.3, January–March 2021) [35], and a high compliance to COVID-19 preventive measures in Thailand [36].
The odds of a COVID-19 positive diagnosis among all individuals tested or not tested found increased with urban residence, higher perceived economic status, being a student or worker in the health sector, moderate or severe psychological symptoms, and not residing in Malaysia, Thailand or five African countries. We did not find a significant association between older age and having comorbidities and a COVID-19 positive diagnosis, as found in the Canadian study [2]. Other studies have likewise found that those who reside in urban areas are more likely to contract the COVID-19 virus compared to rural areas and small towns [37, 38]. This has been attributed to population density and the occurrence of large gatherings more common in urban areas, which accelerated the disease transmission through respiratory droplets in crowded conditions [39]. The higher odds of those who have higher perceived economic status being COVID-19 positive may be attributed to their higher likelihood of being tested, as was found in this study and in another study in New York City [40]. These results may point to the disparity in healthcare access, in which individuals from a higher socioeconomic status have better chances of being tested positive and therefore able to seek treatment. Finally, it is not surprising that workers and students in the healthcare sectors had higher odds of being tested COVID-19 positive due to their higher exposure to the COVID-19 virus.
Like the UK study [3], we found that having comorbidities increased the odds of COVID-19 testing but not with the risk of testing positive. This finding may suggest that having comorbidities may assist in predicting the risk of developing COVID-19 symptoms, and therefore the probability of getting a COVID-19 test [3]. In a study in Bangladesh, underlying health conditions/non-communicable diseases triggered factors for anxiety and depression symptoms. This worry/ fear might be responsible for a higher uptake in testing [41].
Higher education was found associated with COVID-testing uptake, but within the tested population lower education predicted a COVID-19 positive diagnosis. Individuals with lower education may be involved in manual or outdoor jobs which expose them to crowded working conditions (such as in factories), compared to those who have a higher education who may have the opportunity to work from their homes, and have more possibilities to adapt their working conditions to the pandemic situation [42, 43]. In addition, adherence to preventive measures has also been found to be lower among individuals with lower educational attainment [43]. Comparing COVID-19 positive diagnosis among those who tested and the whole sample, including those that had not tested, we found similarities on country, age, sex, living status, chronic conditions, not adhering to four COVID-19 preventive measures, correct COVID-19 knowledge, psychological distress and worry/fear about being (re)infected with COVID-19, but we also found differences in terms of higher education negatively associated with COVID-19 positive diagnosis within the tested population, and an association between urban residence, higher perceived economic status, being a student or worker in the health care sector and COVID-19 positive diagnosis in the whole study population. Health care workers have been identified as a high-risk group for contracting and spreading the COVID-19 virus, due to exposure to symptomatic and asymptomatic patients in healthcare settings, a lack of adherence to preventive measures, and the lack of personal protective equipment [4].
Although a high proportion (51.7%) of participants were very or extremely worried about being (re)infected with COVID-19, this translated only in the unadjusted analysis to higher odds of COVID-19 testing uptake, while higher psychological distress was associated with higher COVID-19 testing, and more severe psychological distress with a COVID-19 positive diagnosis. Individuals who have contracted the virus were found to exhibit more depression and anxiety symptoms in other studies. In a study in Italy among adults surviving COVID-19 infection, 31% presented depression symptoms and 42% anxiety symptoms [44]. It is possible that the psychological distress increased after COVID-19 positive diagnosis, but since survey was only a cross-sectional study, we are not able to determine the direction of the relationship between psychological distress, testing and testing positive. However, within the tested population, psychological distress was inversely associated with a COVID-19 negative diagnosis (analysis not shown).
Study limitations
Our study respondents cannot be considered representative of the general population in the study countries since respondents needed to have had access to the internet to participate in the online survey. We acknowledged this limitation of this study and do believe that studies like this one help in health surveillance actions, which directly impact the evolution of the pandemic in a country and the selection of more assertive preventive measures. Moreover, self-reports, including the outcome variable COVID-19 testing, may be influenced by recall bias and social desirability. Another potential limitation was the poor quality of certain data, e.g., the informational quality of information provided by health care personnel and other information sources. In addition, cultural differences between countries and between regions of the same country can be a limitation in relation to the quality of the information. We also have no information on the type of test used for COVID-19 testing, limiting the accuracy and authenticity of the test results. Some variables, such as COVID-19 symptoms, previous use of health care services, obesity, and smoking, that have been found affecting COVID-19 testing uptake [2, 3] were not assessed in this survey and should be included in future studies.