key: cord-0913095-eynbp9zm
authors: Zakianis; Adzania, Fajriah Hanika; Fauzia, Sifa; Aryati, Gita Permata; Mahkota, Renti
title: Sociodemographic and environmental health risk factor of COVID-19 in Jakarta, Indonesia: An ecological study
date: 2021-08-15
journal: One Health
DOI: 10.1016/j.onehlt.2021.100303
sha: 9647651fe7fb427d1428cedd1aa7644189174bf4
doc_id: 913095
cord_uid: eynbp9zm

Since December 2019, the COVID-19 pandemic has rapidly emerged on a global scale. Many factors have influenced the spread of COVID-19. This research studies the sociodemographic and environmental health risk factors associated with COVID-19. The study used an ecological study design with subdistricts as its unit of analysis. The total population was 44 subdistricts. Data analysis used correlation and linear regression tests. The study results showed that the average COVID-19 incident rate in Jakarta is 99.8 per 10,000 population. Risk factors for the spread of COVID-19 were associated with population's high level of education (B = 3.094, p value<0.001), population density (B = 0.275, p value = 0.029), and slum area (B = 0.404, p value<0.001). The main risk factor for the spread of COVID-19 in Jakarta is high level of education, which can reflect a higher economic status to the population and a tendency to be more mobile. The government needs to enforce a mobility restriction to lessen the spread of COVID-19.

Environmental health conditions could pose a risk to people's vulnerability in facing the COVID-19 pandemic. Environmental health factors include safe water quantity and quality, sanitation, and waste management as environmental health factors that affect transmission (OECD, 2020) . In addition to physical distancing and mask usage, handwashing with soap and running water is also a preventive measure at an individual level (UNICEF-WHO, 2020) . During the COVID-19 pandemic, adequate water supply is essential for ensuring the fulfillment of water demand for sanitation and handwashing purposes. Households that do not have access to safe water are one of the factors contributing to COVID-19 cases (Warner, Zhang & Gonz, 2020) .

In the domestic waste management aspect, COVID-19 prevention measures performed at home resulted in the production of medical waste mixed with domestic waste. The use of a disposable mask can prevent droplets from being inhaled directly (Zhou, 2020) . Alternatively, there is an increase in household medical waste production, especially masks and cleaning products bottle waste (Saadat et al., 2020) . Quarantine policies in various countries resulted in shifting from conventional shopping to online shopping, which eventually increases packaging or inorganic waste at the household level (Zambrano-monserrate et al., 2020) . In Indonesia, the imposed self-quarantine policy performed at home by patients with confirmed COVID-19 cases (Menteri Kesehatan RI, 2020) potentially causes medical and domestic waste mixing. Waste produced by COVID-19 patients contains coronavirus, which can be the infection source (Zambrano-monserrate et al., 2020) . In order to minimize exposure to potentially harmful or infectious waste, there needs to be an efficient waste management system at the household level.

One aspect of good waste management to increase overall public health is the presence of good J o u r n a l P r e -p r o o f Journal Pre-proof waste transportation by waste officers at the household level (Wilson et al., 2015; Taweesan et al., 2016; Asian Development Bank, 2013; Hoornweg & Bhada-Tata, 2012) .

Good sanitation is vital to COVID-19 prevention. The presence of coronavirus in confirmed patient's feces indicates the possibility of fecal-oral transmission; thus, there need to be safety measures to avoid contact with patient feces (Zhou, 2020). Patient's feces, urine, and other waste need to be managed correctly by good sanitation facilities that ensure privacy and Jakarta, which became one of the first area with positive COVID-19 cases in Indonesia, has also become the province with the highest number of positive cases. The number of cases is the accumulation of cases in Jakarta's subdistricts throughout 2020, where the lowest number of cases was found in the South Kepulauan Seribu subdistrict (53 cases), and the highest was in the Cengkareng subdistrict (4,371 cases). With 44 districts and 267 subdistricts, the average confirmed cases per subdistrict in Jakarta were 2,327 (Jakarta Provincial Health Office, 2021).

Multiple prior studies have observed relation between social-demographic factors and COVID-19 spread rate in England, where low education and economic level were related to the spread rate (Chadeau-Hyam et al., 2020) . Nonetheless, we believe that the result will be different from previous studies because Jakarta is a melting pot in Indonesia that has various culture and ethnicity which indirectly affects the socio-demographic aspects there. However, there is limited study regarding socio-demographic and environmental health risk factors of COVID-19, especially in Jakarta. Thus, this study further analyse the relationship between the sociodemographic and environmental health risk factors of the COVID-19 spread in Jakarta.

This study was an ecological study with subdistricts as the unit of analysis. The dependent variable was the COVID-19 incidence rate per 10,000 residents in each subdistrict of Jakarta. Due to the limited data available, the independent variables were socio-demographic risk factors, including the proportions of different education levels, population density in each subdistrict, settlements on riverbanks, and families living in slums in each subdistrict.

Environmental health risk factors measured in this study included the proportion of households using piped water sources, household waste transport by officers, households using latrines, and households that own infiltration holes as liquid waste disposal. The calculation of each variable and data source can be found in Table 1 . Data were presented in tables based on distribution per variable for the dependent and independent variables. Data were analyzed using correlation and linear regression tests (Jr. et al., 2014 

The average number of confirmed positive cases per subdistrict was 2,327 people, or 1% of the population. The incidence rate of COVID-19 per 10,000 people in Jakarta was higher compared to Indonesia's national average of only 21 per 10,000 people. The lowest incidence rate of COVID-19 in Jakarta was found in the North Kepulauan Seribu subdistrict (37.91 per 10,000 people), while the highest was found in the Cempaka Putih subdistrict (179.39 per 10,000 people).

The average proportion of the population with secondary level education was 59%, higher than the national average of 48%. In addition, the average proportion of the population with higher education level was 17%, higher than the national average of 13% (Statistics Indonesia, 2020). The average population density in Jakarta was very high, reaching 8,500

persons/km 2 (BPS, 2010) or more than 1,000 persons/km 2 (Ge & Feng, 2010), and higher than Indonesia's national average population density (140 people/km 2 ; Statistics Indonesia, n.d). The average number of people living in slums in Jakarta was 6%, lower than the national average of 8%

(Statistics Indonesia, 2019). Meanwhile, the average population in Jakarta who lives near the riverbank area was 1%.

J o u r n a l P r e -p r o o f The average proportion of latrine usage and waste transport by officers showed an excellent result of 100% (Wilson et al., 2015) . In Jakarta, the proportion of clean water piping was still categorized as poor, with only 40% coverage (Johnston, 2017) . 

Based on the data presented in Table 3 , the correlation test result between the proportion of low education level, higher education level, very high population density, and slum areas with COVID-19 incidence rate had a significant value of <0.05, which shows a significant correlation.

The strength of the relation could be seen from the correlation coefficient value. In the low education level proportion with COVID-19 incidence rate, the correlation coefficient was -0.627 (significant level<0.001), showing that the relation between both data was 62.7% negatively related very significantly, meaning that the lower proportion of primary education level will result in a higher incidence rate of COVID-19. Linear regression result showed that the independent variables that entered the final regression model were the proportion of low education level, higher education level, high population density, and slum area ( Table 4 ). The determinant coefficient (R squared) showed a value of 0.568, meaning that the regression model can explain that having higher education level and living in slum area with high population density increase 56.8% of COVID-19 incidence rate (Table 4 ). Meanwhile, higher education level alone can increase the incidence rate of COVID-19 to 68%. 

The study results showed that higher level of education is related to the occurrence of COVID-19. The results showed a different outcome from a study conducted in England, where a low education level was related to COVID-19-positive test results (Chadeau-Hyam et al., 2020) .

One of the indicators of higher socioeconomic status was residents who can work and travel (Isdijoso, 2016) . People with higher education levels tend to have office-based jobs and work in office areas. Jakarta has imposed Large-Scale Social Restrictions since March 2020; however, since the 5 th June 2020, workers had been able to normally operate in their offices with a maximum capacity of 50% (Ministry of State-Owned Enterprises Republic of Indonesia, 2020).

In July 2020, 68 reported cases of COVID-19 occurred due to office clustering, with 440 workers diagnosed as COVID-19 positive (Detikhealth, 2020) . In addition, because people who have a higher level of education generally have a better socioeconomic status, they generally tend to have high mobility (Abel et al., 2018; Rustariyuni, 2013) , which increased the risk of J o u r n a l P r e -p r o o f Journal Pre-proof COVID-19 infection (Ariawan & Adisasmito, 2020; Nugraheny, 2020) . Accordingly, people traveling outside home could increase the risk of COVID-19 transmission and spread (CDC, 2021) .

The level of population density was related to COVID-19 occurrence. The result was in line with previous study conducted in Aljazair (2020) which showed strong correlation between population density and the number of positive COVID-19 cases (Kadi, 2020) . One of the preventive measures against COVID-19 infection involved maintaining a physical distance of at least 1.6-2 meters (CDC, 2020). High population density made physical distancing difficult, thus increasing the transmission rate of COVID-19.

A relationship also found between slum areas and COVID-19 cases. Slums were characterized by residential areas that do not have adequate access to safe water, improper sanitation, poor housing quality, high population density, and illegal housing status (UN-Habitat, 2016) . Settlements with high population density and lack of adequate sanitation could increase the risk of COVID-19 transmission (Ahmad et al., 2020) . Residential settlement conditions were also one of the socioeconomic determinants. Previous studies in the United States stated that groups with low socioeconomic had a higher risk of being infected with COVID-19 because the group was affected by comorbid diseases that could worsen the condition. In times of communicable disease pandemics such as COVID-19, distance restrictions should be applied on a large scale worldwide. However, this was unlikely in slums due to the high density of buildings in the area (Friesen, 2020) .

The correlation test result between the proportion of households with piped water as a source of drinking water and clean water showed no significance with COVID-19 infection. This could happen because COVID-19 was being transmitted through droplets instead of water (WHO, J o u r n a l P r e -p r o o f Journal Pre-proof 2020). In COVID-19 prevention, water is needed to wash hands. However, people can use hand sanitizer if water was not available for washing hands (UNICEF, 2020). The consistency and accessibility of Jakarta's piped water supply are both low. In Jakarta, less than a third of the population has access to piped water in their homes (Colbran, 2017) . Based on statistics by Statistics Indonesia, besides metered pipe water (PAM/PDAM) people in Jakarta got clean water from non-metered piping (2%) and ground water using pumps (58%) (Statistics Indonesia, 2018).

Risk factors related to the spread of COVID-19 were the level of higher education, population density, and slum area. This was supported by a previous study conducted in Kenya, which showed that slum dwellers had worse health and socioeconomic conditions than other social groups due to limited access to education, employment, water, and sanitation (Lukeman et al., 2014) . Therefore, efforts were needed to prevent the spread of COVID-19 by ensuring the availability of safe water, good management of waste, and the need to improve hygiene in slums (UNICEF-WHO, 2020).

The use of correlation study design limited the study to only utilize aggregate data; thus, the data obtained only applies to a certain population and was unable to represent individual exposure specifically. Moreover, this study's correlation study design could only examine the initial relationship between independent and dependent variables. The results shown in this study only described the initial severity of the studied variables. Therefore, further research is needed on the causal relationship between independent and dependent variables at an individual level, for example, using a cross-sectional, case-control, or cohort design. Independent variables should be added in accordance with previous research, such as household income levels, food safety and malnutrition, social protection, cost and distance, access to healthcare facilities, and social isolation (Duarte et al., 2021) .

Based on this study, factors related to COVID-19 cases in Jakarta were higher education level, population density, and slums. There needs to be a unique approach for residents with higher education levels, especially those with high office activity and mobility levels. Strict regulations on mobility restrictions need to be enforced. Governments in areas with high-level population density must increase public awareness to avoid crowds and maintain personal and environmental hygiene. These local governments should also forbid self-isolation at home for those with non-symptomatic COVID-19. Instead, they need to provide designated isolation locations. In the future, the government is encouraged to organize slums, especially regarding environmental health, such as providing safe water quality and efficient waste and liquid waste management. In addition, local governments are expected to provide decent and affordable housing for the poor.

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