1 PB
1 PB
1 PB
Izza Suraya1, Mochamad Iqbal Nurmansyah2, Nia Musniati1, Elia Nur Ayunin1, Catur
Rosidati2, and Ibrahim Isa Koire3
1
Faculty of Health Sciences, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta,
2
Faculty of Health Sciences, Universitas Islam Negeri Syarif Hidayatullah, Jakarta,
3
Institute of Science, Istanbul University, Turkey
Abstract
Indonesia is a country with the highest COVID-19 confirmed cases and mortality rate among
southeast Asian countries. This study was conducted to identify the correlation between
sociodemographic factors and the number of confirmed cases and mortality rates due to
COVID-19 in Indonesia. This research is an ecological study where secondary data published
by the Indonesian government was used. Spearman correlation were used in this study.
This study showed that sociodemographic conditions in Indonesia varied greatly. Spearman
correlation test results showed that a significant relationship (p-value < 0.05) between
the number of COVID-19 confirmation cases with population density, population growth,
decreased mobility outside the home, hypertension and diabetes prevalence, number of
health workers (general practitioners, specialist doctors, and nurses) as well as the number
of COVID-19 specialized hospitals. Significant correlations (p-value < 0.05) were also shown
by the relationship between COVID-19 mortality rates and a dense population, a large
decrease in mobility to the workplace, number of smokers, and number of health workers.
Equitable development is expected to reduce sociodemographic and health disparities so
that each region has good preparedness in dealing with outbreaks without the occurrence of
areas that are more severely affected by outbreaks compared to other regions.
not been effective in reducing COVID-19 eastern part of Indonesia, has both the lowest
cases in several regions in Indonesia absolute number of general practitioners’
(Ariawan, 2020). The ineffectiveness of the doctors (GPs) and the lowest doctors per
interventions was indicated by the continued 1000 population (Mahendradhata et al.,
high mobility of the population in various 2017). The distribution of medical specialist
regions in Indonesia (Ariawan, 2020). was more concentrated in large provinces
Indonesia’s COVID-19 case mortality at the on the island of Java and Bali, while the
middle of December were at the highest three provinces with the lowest distribution of
death toll in the Southeast Asian region with medical specialists were North Maluku, West
a total of 19,248 fatalities, surpassing other Sulawesi, and East Nusa Tenggara (NTT)
ASEAN countries’ COVID-19 deaths (Dezan with 3.9, 3.5, 3.2 per 100.000 population
Shira and Associates, 2020). respectively (Slamet, 2018). WHO stated
The high number of smokers and that geographical inequality in health facility
presence of underlying diseases are and personnel is high in Indonesia (World
factors that contribute to the high number of Health Organization, 2017). In addition,
COVID-19 deaths in Indonesia (Brake et al., complete basic immunization coverage
2020; WHO Indonesia, 2020). Based on the was low nationally, and demonstrated a
2018 Indonesian Basic Health Survey, 63% large inequality, especially depending on
Indonesian adult men were smoker (Health sub-national region and economic status
Research and Development Agency of the (World Health Organization, 2017). Under-
Republic of Indonesia, 2019). The report five mortality rates in the eastern regions of
also stated that cardio vascular diseases and Indonesia (West Sulawesi, Maluku, and West
diabetes were among the highest disease Nusa Tenggara) were more than four times
burdens of the country Health Research higher than those in the western regions
and Development Agency of the Republic of (Central Java and Yogyakarta) (Johar et al.,
Indonesia, 2019). 2018). Therefore, with lower levels of several
Regional disparities within its health health indicators, the eastern regions of
system was allegedly responsible for the high Indonesia tend to be at a more disadvantage
number of COVID-19 cases (Wahyuni, 2020). (World Health Organization, 2017).
Indonesia has the sixth worst wealth inequality In outbreaks of infectious diseases, hard
in the world (Gibson, 2017). The growth of social and economic conditions contribute
cities seems to occur more rapidly in Java to the unpreparedness of different groups of
and the western part of Indonesia compared people to respond to these outbreaks (Bolin &
to outside Java and other eastern Indonesian Kurtz, 2018). Therefore, it may be worthwhile
regions (Wilonoyudho et al., 2017). World to address how health inequalities between
Health Organization highlighted differences sub-national regions in Indonesia affected
in health statuses and distribution of health and contributed in the COVID-19 cases and
resources across the sub-national regions of deaths. The study may help to understand
Indonesia (World Health Organization, 2017). the demographic impact on different patterns
In the context of numbers and distribution of of case numbers and mortality between
doctors, DKI Jakarta province as the capital regions (Balbo et al., 2020). Thus, this study
city has the highest number of doctors as well aimed at assessing correlation between
as the highest ratio of doctors to population sociodemographics and health related
(Mahendradhata et al., 2017). In contrast, conditions with COVID-19 cases and deaths
West Sulawesi province which is located in the in Indonesia.
Figure 2. COVID-19 Case Fatality Rate by Province in Indonesia (Per 17 June 2020)
Based on the population mobility on June had 22,118 nurses. The gap in the number
6, 2020, there was a diversity of changes of general practitioners was also wide,
in population mobility. Having compared to amounting to 1,642 (with a value of σ2 =
mobility on the baseline (April 25, 2020), 159,917.09), while that of specialist doctors
all provinces had decreased mobility to was 1,655 (with σ2 = 196,310.86). The
workplaces, wholesalers, recreation, parks, existence of special health facilities for
and transit stations. However, mobility to handling COVID-19 in each province also
shopping, staples and medicines, stations varied. Even though the ratio of beds to 1000
and workplaces in several provinces population was homogeneous, the number
experienced an increase compared to the of specialized COVID-19 hospitals was very
baseline. The opposite condition occurred heterogeneous, with some provinces having
with the mobility towards residential areas, only 1 hospital while other provinces had 105
where all provinces experienced an increase hospitals (σ2 = 575. 26).
in the movement towards housing on 6 June
2020 with a range of change from 6% to 16%. Bivariate Analysis
Table 1 also showed variations in the
proportion of behavior related to health The results of the Spearman correlation
problems in Indonesia. The table shows that between the independent variables and the
basic immunization coverage in Indonesia COVID-19 confirmed cases are shown in Table
was uneven (σ2 = 114, 01), with some areas 2. There are 14 out of 26 independent variables
showing basic immunization coverage that showed a significant relationship. On the
of 20.18%, while other regions reached sociodemographic dimension, the provinces
64.79%. The percentage of smokers in each with high population density tended to have
province was diverse, ranging from 19.75% high COVID 19 confirmed cases (ρ = 0.717;
- 33.86% (σ2 = 10.15). Heterogeneity was p-value = 0.000) (Figure 3). The growth rate
also seen in the prevalence of hypertension variable showed the opposite, with provinces
(σ2 = 22.64) and stroke (σ2 = 7.34), while a that had low growth rates tending to have
more homogeneous value was seen in the high confirmed cases (ρ = -0.467; p-value =
prevalence of asthma (σ2 = 0.59), CHD (σ2 0.003). Provinces that had increased mobility
= 0.16), and diabetes (σ2 = 0.25). towards residential areas on June 6, 2020
In addition, there was inequality in the tended to have high confirmed cases (ρ =
distribution of health workers for handling 0.701; p-value = 0.000) (Figure 4). However,
COVID-19. With a variance value (σ2) of = provinces that had decreased mobility
30,319,902.89, there was one province that outside the home also tended to have high
only had 161 nurses working in specialized confirmed cases.
COVID-19 hospitals, while other provinces
Figure 3. Scatter plot and Spearman correlation coefficient (r) of Population Density and
COVID-19 Confirmed Cases
Figure 4. Scatter plot and Spearman correlation coefficient (r) of Mobility for Residential
and COVID-19 Confirmed Cases
Populasi Volume 29 Issue 1 2021 25
Izza Suraya, Mochamad Iqbal Nurmansyah, Nia Musniati, Elia Nur Ayunin,
Catur Rosidati, and Ibrahim Isa Koire
The health conditions variable was cases. In addition, provinces with high ratio
noted, with provinces that had high of government primary healthcare in sub-
prevalence of diabetes and high hypertension districts had high confirmed cases (ρ = 0.691;
having high COVID-19 confirmed cases. p-value = 0.000). This was also observed
In addition, the number of health workers with the number of COVID-19 specialized
such as doctors, specialists and nurses also hospitals (ρ = 0.448; p value = 0.004).
showed a strong positive correlation with Table 2 also shows the relationship
COVID-19 case number (with ρ> 0.6). This between the independent variables with
meant that provinces that had many health COVID-19 fatality rate. There was 7 out of 26
workers tended to detect more confirmed variables showing a significant correlation.
26 Populasi Volume 29 Issue 1 2021
Sociodemographic and Health-related Determinants of COVID-19 Prevalence
and Case Fatality Rate in Indonesia
Figure 5. Scatter plot and Spearman correlation coefficient (r) of Smoker Prevalence and
COVID-19 Case Fatality Rate
Jakarta, which has the highest COVID-19 people from Jakarta-Bekasi (West Java) and
cases, has a population density that is Jakarta-Banten during the implementation
much higher than the population density of large-scale social restriction policy had
of Indonesia; with the population density not changed much compared to the period
of Jakarta reaching 16,704 inhabitants km² before the policy was enacted (Suryahudaya,
while Indonesia’s population density is 141 2020). Jakarta being the centre of Indonesia’s
inhabitants/km² (Akbar, 2020). Related to economy, attracts people’s mobility from
density, one of the conditions that can be the neighboring provinces towards it for
a cluster of transmission of COVID-19 in work or school. A report from the Statistics
Indonesia are the traditional markets (Girsang Indonesian showed that 29.3 million people
et al., 2020). In addition to the increased in Jakarta, Bogor, Depok, Tangerang,
population density in traditional markets, Bekasi (these 4 cities are cities that border
where it is difficult to maintain physical directly with Jakarta) were commuters, with
distance, lack of community compliance in south Jakarta being the biggest commuter
implementing COVID-19 prevention protocols destination (Subdirektorat Statistik Mobilitas
such as regular hand washing and wearing Penduduk dan Tenaga Kerja, 2019).
masks, increases the likelihood of traditional A report from the Department of
markets to act as clusters of COVID-19 Transportation in the Jakarta Province also
transmission. showed that the number of vehicles entering
The percentage of older population had Jakarta from West Java and Banten during
no significant correlation with the increase in the second period of the large-scale social
COVID-19 cases; since COVID-19 cases in restriction was still high (Rahmawati, 2020).
Indonesia were dominated by the productive Despite the implementation of a large-
age (31-45 years) (Hidayati, 2020). However, scale social restriction policy, community
due to the changes in the physiological compliance with these regulations in the
functions of the respiratory system and policy was inadequate. This is indicated by
decreased immunity made older people with the fact that there were many people leaving
COVID-19 had worse clinical manifestations, their houses without wearing masks, with
greater severity and longer disease courses non-essential workplaces still operating. In
(Liu et al., 2020). Jakarta, the government found from 1 to 14
Due to the government’s policy of September 2020, there were more than 6000
implementation of large-scale social violation of the large-scale social restrictions
restrictions, it has had an impact on reducing (Saidah, 2020). For information, during the
the mobility of the population to various places large-scale social restriction, schools and
such as workplaces, recreation, grocery, workplaces (exempting central government
and transit stations. The increase in mobility offices, businesses and transportation
in the residential areas had a significant companies that serve public essential needs)
effect on the increase in COVID-19 cases, were closed, religious activities that involve
as observed in a previous study that showed mass gatherings, modes of transportation,
that the family was among the COVID-19 activities in public places or facilities were
transmission routes (Xiong et al., 2020). limited and everyone who goes out of the
However, we assumed that although there house was required to use a mask. A previous
has been a decline in mobility compared to study showed that timely implementation with
the baseline mobility, population mobility to high compliance from the community could
various places (such as workplaces and other be a factor in the successful implementation
places) is still quite high. A study performed in of non-pharmaceutical interventions (Fong et
Jakarta, Indonesia showed that movement of al., 2020). Therefore, the ineffectiveness of
the PSBB in reducing COVID-19 cases was Later, Provinces that had high
not derived from misconceptions and rules prevalence of diabetes and hypertension
issued, but rather to the lack of community tended to have high COVID-19 confirmed
compliance with regulations such as wearing cases. A study that examined around 5,000
masks and maintaining physical distance. COVID-19 patients in New York City and
The underlying conditions to describe the the nearby areas showed that high blood
people’s lack of implementation of the PSBB pressure, obesity and diabetes were the
protocol were complicated. Restrictive most common commonalities (Richardson
social and business processes carried et al., 2020). Based on the Indonesian Basic
short and possibly medium-term financial Health Survey, prevalence of diabetes and
burdens (Anderson et al., 2020). The people, hypertension increased in 2018 compared to
particularly those working in the informal 2013 (Badan Penelitian dan Pengembangan
sector should continue to work or open their Kesehatan, 2019). The number of health
business to get income. A previous study workers such as doctors, specialists, and
showed some of the reasons why people nurses in one province also showed a strong
did not practice the social distance, including positive correlation with COVID-19 case
work requirements for non-essential number. This could mean that provinces
industries, engagement in social, physical with many health workers tended to detect
or routine activities and the belief that social more confirmed cases. Data showed that
distancing was not needed if other preventive Indonesia had only conducted SARS-
measures had been performed (Moore et al., CoV-2 tests on 25 people per one million
2020). people; the lowest compared to other Asian
This study found that a proportion countries (Katadata.co.id, 2020). Besides the
of smokers in a province had a positive lack of health infrastructure, the existence of
correlation with mortality due to COVID-19, negative stigma towards people infected with
whereas a previous study showed that COVID-19 discourages them, since they get
smokers were 1.4 times more likely (95% afraid to be shunned or treated badly could
CI: 0.98–2.00) to have severe conditions avoid testing or treatment.
and approximately 2.4 times more likely to The results of this study suggested that
be admitted to an ICU, needed mechanical government should put in heavy efforts on
ventilation or died compared to non-smokers policies related to population development;
(RR=2.4, 95% CI: 1.43–4.04) (Vardavas & like developing regional growth centers
Nikitara, 2020). As showed in this study, the especially in eastern Indonesia and outside
proportion of +15 age years old who smoked Java, so that population growth in each
cigarette in each province was quite diverse subnational region in Indonesia can be
in the range of 19.75% - 33.86%since not all distributed evenly. This in turn will have an
provinces had a smoke free area policy, since impact on the distribution of population
the 2018 data from Ministry of Home Affairs density. During pandemic, the government
of the Republic of Indonesia showed that 22 needed to take various efforts to increase
out of 34 Provinces had local regulations community compliance in implementing
about free area smoke policy (Nainggolan, large-scale social restrictions to reduce
2018). Although the central government community mobility and thereby encouraging
has already issued smoke free policy since communities to be more compliant in
2009, due to a decentralized system in the implementing preventive behavior, which in
Indonesian government, the realization of turn could reduce the number of COVID-19
these regulations at the city level requires cases. In addition, there is need to involve
passage of laws by local governments. various community groups to carry out
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