A spatial-temporal description of the SARS-CoV-2 infections in Indonesia during the first six months of outbreak

Exploring the Spatial and Temporal Patterns of Children and Adolescents with COVID-19 Infections in Slovakia during March 2020 to July 2022

Background and Objectives: The COVID-19 pandemic has had a significant global impact, necessitating a comprehensive understanding of its spatiotemporal patterns. The objective of this study is to explore the spatial and temporal patterns of COVID-19 infections among five age groups (<1, 1-4, 5-9, 10-14, and 15-19 years) in 72 districts of Slovakia on a quarterly basis from March 2020 to July 2022. Material and Methods: During the study period, a total of 393,429 confirmed PCR cases of COVID-19 or positive antigen tests were recorded across all studied age groups. The analysis examined the spatiotemporal spread of COVID infections per quarter, from September 2021 to May 2022. Additionally, data on hospitalizations, intensive care unit (ICU) admissions, pulmonary ventilation (PV), and death cases were analyzed. Results: The highest number of COVID-19 infections occurred between September 2021 and May 2022, particularly in the 10-14-year-old group (68,695 cases), followed by the 15-19-year-old group (62,232 cases), while the lowest incidence was observed in the <1-year-old group (1235 cases). Out of the total confirmed PCR cases, 18,886 individuals required hospitalization, 456 needed ICU admission, 402 received pulmonary ventilation, and only 16 died. The analysis of total daily confirmed PCR cases for all regions showed two major peaks on 12 December 2021 (6114 cases) and 1 February 2022 (3889 cases). Spatial mapping revealed that during December 2021 to February 2022, the highest number of infections in all age groups were concentrated mainly in Bratislava. Moreover, temporal trends of infections within each age group, considering monthly and yearly variations, exhibited distinct spatial patterns, indicating localized outbreaks in specific regions. Conclusions: The spatial and temporal patterns of COVID-19 infections among different age groups in Slovakia showed a higher number of infections in the 10-14-year-old age group, mainly occurring in urban districts. The temporal pattern of the spread of the virus to neighboring urban and rural districts reflected the movement of infected individuals. Hospitalizations, ICU and PV admissions, and deaths were relatively low. The study highlights the need for more proactive measures to contain outbreaks promptly and ensure the resilience of healthcare systems against future pandemics.

Molecular Epidemiology of SARS-CoV-2 within Accra Metropolis Postlockdown

Introduction

Currently, sequencing has been the only tool for the identification of circulating severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) variants. However, it is known to be an expensive and laborious approach involving high technical expertise. Considering the reduced adherence to preventive measures postlockdown in Accra, this study presents an alternative method that leverages polymerase chain reaction (PCR) to identify circulating SARS-CoV-2 variants in the Accra Metropolis postlockdown.

Methods

This prospective cross-sectional study was conducted between July and December 2022. Nasopharyngeal samples were collected from 268 consenting participants. Samples were subjected to nucleic acid extraction and followed by real-time polymerase chain reaction for the detection and quantification of SARS-CoV-2 RNA. SARS-CoV-2 positive samples were subsequently subjected to variant identification using rapid PCR. Findings. The prevalence of SARS-CoV-2 within the Accra Metropolis was 30.2%. The majority of the SARS-CoV-2 infection was diagnosed in females, participants aged 41-50 years, and symptomatic participants. Participants aged ≤10 years and females recorded the highest viral load while participants aged 41-50 years recorded the highest number of infections. The SARS-CoV-2 variants detected were Alpha (64.2%), Delta (22.2%), and Omicron (13.6%). Predictors of SARS-CoV-2 infection identified were chills, cough, headache, body weakness, sore throat, and dyspnoea in order of decreasing association with SARS-CoV-2 infection. There was a strong association between symptom status, gender, age, and SARS-CoV-2 infection.

Conclusion

There was a high prevalence of SARS-CoV-2 within the Accra Metropolis postlockdown within the sampling period. The Alpha variant of SARS-CoV-2 is the predominant circulating variant, and persons presenting with symptoms are most likely to be diagnosed with COVID-19. Children aged ≤10 years serve as a reservoir for infection transmission.

Clinical determinants of oxygen saturation and length of hospitalisation of COVID-19 patients: A cross-sectional study in Indonesia

Aims

Indonesia was one of the countries with the highest COVID-19 positive cases. Understanding the length of hospitalisation is critical for anticipating bed demand and resource allocation, such as oxygen. This study aims to examine the determinants of oxygen saturation and the length of hospitalisation in Hermina Mekarsari Hospital, West Java, Indonesia.

Methods

This cross-sectional study uses medical records from June to August 2021. The inclusion criteria were: COVID-19 patients aged between18 and 65, fully conscious, and not using mechanical ventilation. Participants who passed away during hospital stay were excluded. We used demographic information, laboratory data, and the clinician's assessments of the patients admitted to the hospital. Linear regression was performed for oxygen saturation on day seven, while logistic regression analysis was conducted to predict the length of hospital stay.

Results

In total, 371 participants with an average age of 47.2 (standard deviation 15.8) years were included. Most participants were female (57.7%) and smoking (78.4%). The results indicated that decreasing oxygen saturation was reported in vomiting patients (β = 1.63, p-value = .001), hypertensive patients (β 1.18 with, p-value = .034), and patients with the increased respiratory rate (β = 0.28, p-value = .000). In the logistic regression, we found that respondents who experienced dyspnoea, headache, fever, an increasing number of D-Dimer and blood glucose, and those with diabetes mellitus were more likely to stay more than 14 days.

Conclusions

Oxygen saturation was influenced by vomiting, hypertension, and increasing respiratory rate. Length of hospitalisation of more than 14 days was influenced by dyspnoea, headache, fever, increased number of D-Dimer, blood glucose, and diabetes mellitus. Identifying the determinants of oxygen saturation and length of stay can inform health professionals in designing a suitable intervention to reduce mortality and length of stay among COVID-19 patients in Indonesia.

The Use of Digital Technology for COVID-19 Detection and Response Management in Indonesia: Mixed Methods Study

BACKGROUND

The COVID-19 pandemic has triggered a greater use of digital technologies as part of the health care response in many countries, including Indonesia. It is the world's fourth-most populous nation and Southeast Asia's most populous country, with considerable public health pressures.

OBJECTIVE

The aim of our study is to identify and review the use of digital health technologies in COVID-19 detection and response management in Indonesia.

METHODS

We conducted a literature review of publicly accessible information in technical and scientific journals, as well as news articles from September 2020 to August 2022 to identify the use case examples of digital technologies in COVID-19 detection and response management in Indonesia.

RESULTS

The results are presented in 3 groups, namely (1) big data, artificial intelligence, and machine learning (technologies for the collection or processing of data); (2) health care system technologies (acting at the public health level); and (3) COVID-19 screening, population treatment, and prevention population treatment (acting at the individual patient level). Some of these technologies are the result of government-academia-private sector collaborations during the pandemic, which represent a novel, multisectoral practice in Indonesia within the public health care ecosystem. A small number of the identified technologies pre-existed the pandemic but were upgraded and adapted for current needs.

CONCLUSIONS

Digital technologies were developed in Indonesia during the pandemic, with a direct impact on supporting COVID-19 management, detection, response, and treatment. They addressed different areas of the technological spectrum and with different levels of adoption, ranging from local to regional to national. The indirect impact of this wave of technological creation and use is a strong foundation for fostering future multisectoral collaboration within the national health care system of Indonesia.

Spatial and Temporal Analysis of COVID-19 Cases in West Java, Indonesia and Its Influencing Factors

Coronavirus Disease 2019 (COVID-19) spread quickly and reached epidemic levels worldwide. West Java is Indonesia's most populous province and has a high susceptibility to the transmission of the disease, resulting in a significant number of COVID-19 cases. Therefore, this research aimed to determine the influencing factors as well as the spatial and temporal distribution of COVID-19 in West Java. Data on COVID-19 cases in West Java obtained from PIKOBAR were used. Spatial distribution was described using a choropleth, while the influencing factors were evaluated with regression analysis. To determine whether COVID-19s policies and events affected its temporal distribution, the cases detected were graphed daily or biweekly with information on those two variables. Furthermore, the cumulative incidence was described in the linear regression analysis model as being significantly influenced by vaccinations and greatly elevated by population density. The biweekly chart had a random pattern with sharp decreases or spikes in cumulative incidence changes. Spatial and temporal analysis helps greatly in understanding distribution patterns and their influencing factors, specifically at the beginning of the pandemic. Plans and strategies for control and assessment programs may be supported by this study material.

Geographical variations and district-level factors associated with COVID-19 mortality in Indonesia: a nationwide ecological study

BACKGROUND

Ensuring health equity, especially for vulnerable populations in less developed settings with poor health system is essential for the current and future global health threats. This study examined geographical variations of COVID-19 mortality and its association with population health characteristics, health care capacity in responding pandemic, and socio-economic characteristics across 514 districts in Indonesia.

METHODS

This nationwide ecological study included aggregated data of COVID-19 cases and deaths from all 514 districts in Indonesia, recorded in the National COVID-19 Task Force database, during the first two years of the epidemic, from 1 March 2020 to 27 February 2022. The dependent variable was district-level COVID-19 mortality rate per 100,000 populations. The independent variables include district-level COVID-19 incidence rate, population health, health care capacity, and socio-demographics data from government official sources. We used multivariable ordinal logistic regression to examine factors associated with higher mortality rate.

RESULTS

Of total 5,539,333 reported COVID-19 cases, 148,034 (2.7%) died, and 5,391,299 (97.4%) were recovered. The district-level mortality rate ranged from 0 to 284 deaths per 100,000 populations. The top five districts with the highest mortality rate were Balikpapan (284 deaths per 100,000 populations), Semarang (263), Madiun (254), Magelang (250), and Yogyakarta (247). A higher COVID-19 incidence (coefficient 1.64, 95% CI 1.22 to 1.75), a higher proportion of ≥ 60 years old population (coefficient 0.26, 95% CI 0.06 to 0.46), a higher prevalence of diabetes mellitus (coefficient 0.60, 95% CI 0.37 to 0.84), a lower prevalence of obesity (coefficient -0.32, 95% CI -0.56 to -0.08), a lower number of nurses per population (coefficient -0.27, 95% CI -0.50 to -0.04), a higher number of midwives per population (coefficient 0.32, 95% CI 0.13 to 0.50), and a higher expenditure (coefficient 0.34, 95% CI 0.10 to 0.57) was associated with a higher COVID-19 mortality rate.

CONCLUSION

COVID-19 mortality rate in Indonesia was highly heterogeneous and associated with higher COVID-19 incidence, different prevalence of pre-existing comorbidity, healthcare capacity in responding the pandemic, and socio-economic characteristics. This study revealed the need of controlling both COVID-19 and those known comorbidities, health capacity strengthening, and better resource allocation to ensure optimal health outcomes for vulnerable population.

Building on health security capacities in Indonesia: Lessons learned from the COVID-19 pandemic responses and challenges

As an active member country of the WHO's International Health Regulation and Global Health Security Agenda, Indonesia, the world's fourth-most populous and largest archipelagic country has recorded the second-highest COVID-19 cases in Asia with over 1.8 million cases in early June 2021. This geographically and socially diverse country has a dynamic national and sub-national government coordination with decentralized authorities that can complicate a pandemic response which often requires nationally harmonized policies, adaptability to sub-national contexts and global interconnectedness. This paper analyses and reviews COVID-19 public data, regulations, guidance documents, statements and other related official documents to present a narrative that summarizes the government's COVID-19 response strategies. It further analyses the challenges and achievements of the country's zoonotic diseases preparedness and responses and lastly provides relevant recommendations. Findings are presented in four sections according to the Global Health Security Agenda capacities, namely epidemiological surveillance (detect capacity); laboratory diagnostic testing (respond capacity); data management and analysis (enable capacity); and the role of sub-national governments. The COVID-19 pandemic has been a catalyst for the rapid transformation of existing surveillance systems, inter-related stakeholder coordination and agile development from the pre-pandemic health security capacities. This paper offers several recommendations on surveillance, laboratory capacity and data management, which might be useful for Indonesia and other countries with similar characteristics beyond the COVID-19 response, such as achieving long-term health security, zoonoses and pandemic prevention, as well as a digital transformation of their governmental capacities.

The Prevalence and the Associated Sociodemographic-Occupational Factors of Professional Burnout Among Health Professionals During COVID-19 Pandemic in Malang, Indonesia: A Cross-Sectional Study

Background

Since 2020, Indonesian health professionals have been affected by burnout as the physiological impact due to the COVID-19 pandemic. Malang has contributed to a substantial number of new daily cases and death rates in East Java, an epicenter of COVID-19 in Indonesia. However, a study about how burnout affected Malang health professionals was never conducted.

Objectives

This research aimed to assess the prevalence and factors associated with burnout among health professionals during the COVID-19 pandemic in Malang, Indonesia.

Materials and Methods

A cross-sectional study was carried out with an online survey conducted in 5 major hospitals in Malang. We conducted a study about the prevalence rate of burnout in Malang and the association between sociodemographic factors, occupational hazards, and the Maslach Burnout Inventory-Human Services Survey (MBI-HSS). The associations were presented as odds ratio (OR) and 95% confidence interval (CI).

Results

We analyzed 1,077 health professionals in Malang. Our result showed that the prevalence of burnout among health professionals in Malang is 22.0%. Respondents under the age of 30 tend to experience a higher level of burnout by 3.4-fold (OR = 3.43, p-value < 0.001), compared with those over the age of 40 years. Our data showed that respondents working longer than 100 h/week tend to experience burnout by 3.8-fold (OR = 3.83, p-value < 0.001).

Conclusion

Approximately one-fifth of the health professionals in Malang suffered from burnout during the COVID-19 pandemic, and MBI-HSS subscales are strongly associated with age and work hours.

Prevalence and epidemiological characteristics of COVID-19 after one year of pandemic in Jakarta and neighbouring areas, Indonesia: A single center study

We determined the prevalence and epidemiological characteristics of COVID-19 in Jakarta and neighboring areas, Indonesia from March 2020 to February 2021, based on nasopharyngeal/oropharyngeal (NP/OP) swab specimens that were tested at the Eijkman Institute for Molecular Biology, Jakarta. NP/OP swab specimens were collected from COVID-19 suspects or individuals in contact tracing programs from primary healthcare centers (PHC) and hospitals. The specimens were screened for the SARS-CoV-2 by qRT-PCR. Demography data and clinical symptoms were collected using national standardized laboratory form. Of 64,364 specimens, 10,130 (15.7%) were confirmed positive for SARS-CoV-2, with the peak prevalence of infection in March 2020 (26.3%) follow by in January 2021 (23.9%) and February 2021 (21.8%). We found that the positivity rate of the specimens from Jakarta, West Java, and Banten was 16.3%, 13.3%, and 16.8%, respectively. Positivity rate was higher in specimens from hospitals (16.9%) than PHC (9.4%). Of the positive specimens, 29.6% were from individuals aged >60 years old, followed by individuals aged 41-60 years old (24.2%). Among symptomatic cases of SARS-CoV-2, the most common symptoms were cough, fever, and a combination of both cough & fever. In conclusion, this study illustrates the prevalence and epidemiological characteristics from one COVID-19 diagnostic center in Jakarta and neighbouring areas in Indonesia.

The Effect of Educational Video on COVID-19 and Dental Emergency Literacy among Students during Pandemic Era

OBJECTIVES

 To determine (1) the level of knowledge regarding COVID-19 and dental emergency (DE) along with the factors that might be associated (2) with the effect of educational video on the level of knowledge among nondental students.

MATERIALS AND METHODS

 This online pre-experimental study used an educational video regarding COVID-19 and DE with a one-group pretest-posttest design toward the undergraduate nondental students (n = 363) from six public universities in West Java Province, Indonesia, aged 18 to 22 years. A Google Form was used and convenience sampling was undertaken.

STATISTICAL ANALYSIS

 The chi-squared, Mann-Whitney, Wilcoxon, and Spearman correlation tests were performed. Cohen's d effect size was used to assess the effect of videos.

RESULTS

 Most of the respondents were females around 20.36 ± 0.94 years. There is a statistically significant difference between the pre- and posttest knowledge score for COVID-19 (p <0.001) and DE (p <0.001). The "with dental school" group had a significantly higher pretest score in DE literacy than the "without dental school" group. There is a significantly positive linear relationship between the frequency of watching videos and the posttest score. The effect size was 1.03 and 0.8 for COVID-19 and DE, respectively. The majority of students agreed (agree and very agree) with all statements regarding video education.

CONCLUSIONS

 The level of knowledge regarding COVID-19 and DE increased from 5.30 to 6.75 and 6.58 to 8.02, respectively. The associated factors were the type of university and the frequency of watching videos. Educational intervention seems to have a great effect in increasing the knowledge of nondental students.

Extent of COVID-19 Healthcare Services of Isolation Center of Private Hospital across Khartoum State, Sudan

Introduction

Spatial presentation is considered a useful tool for analyzing and mapping the frequencies of incidences of different pathogens. Khartoum State accounted for 78% of the overall cases of COVID-19 in Sudan. The aim of this study was to present the spatial extent of healthcare services of a private isolation center during the pandemic at the locality level.

Materials and Methods

A spatial descriptive study was conducted using ArcGIS to present the locations of all COVID-19 patients who attended Imperial Hospital isolation center on November–December 2020 in Khartoum, Sudan.

Results

Patients diagnosed with COVID-19 during the study period were 188; they had attended Imperial Hospital from 9 states. Patients from Khartoum State were 167 patients. Of those 167 patients, 75 were from the Khartoum locality; it is the locality in which Imperial Hospital is located, followed by Khartoum Bahri (34 patients), Omdurman (19 patients), and South Khartoum (14 patients), while 10 patients each were from the Sharg En Nile and Karary localities.

Conclusion

Patients from 8 different states of Sudan had travelled to reach Khartoum State to get health services. At the state level, Khartoum State was the most benefited state from the healthcare services of Imperial Hospital. At a locality level, Khartoum locality was the most benefited one.

Sustained Actions in Combating Neglected Tropical Diseases during the COVID-19 Pandemic: Lessons Learned From the Leprosy Program in the Hyper-Endemic Area in Papua Province, Indonesia

In 2020 we witnessed the global pandemic of COVID-19. Papua, Indonesia announced the first case of COVID-19 on 7 March 2020, and reached 41,137 positive cases with a total of 1,183 fatality cases in August 2021. In the midst of the effort to handle COVID-19, this area of hyper-endemic tropical diseases, including leprosy, has also had to cope with these established problems. Some leprosy indicators have shown decreased performance. The new case detection rate (NCDR) per 100,000 population in Papua Province decreased from 45.36 in 2019 to 29.75 in December 2020. Grade 2 disability (G2D) proportion amongst the new cases increased from 9.0% in 2019 to 11.4% in 2020. There was a 27% decrease of the proportion of child leprosy, following the decrease of elementary school surveys from 6.1% in 2019 to only 1.0% in 2020. Although precautions should be taken, it should be done to minimalize impacts not only for the current pandemic, but also the existing neglected tropical diseases (NTDs). The central government should optimize their functions as a control system to maintain standard services and to monitor the local health authority. The current guidelines regarding implementation of NTD programs during the COVID-19 pandemic should be evaluated and revised, and followed by adequate explanation and proper training to accommodate better services. Emphasis on prevention and early detection should be considered as the main way forward to strengthen the health system.

SARS-CoV-2 Variants of Concern Increased Transmission and Decrease Vaccine Efficacy in the COVID-19 Pandemic in Palembang Indonesia

BACKGROUND AND AIM

The number of COVID-19 cases surging despite the large scale of health promotion campaigns. This study aimed to find disease transmissibility and affected vaccine efficacy associated with the mutation of the SARS-CoV-2 variant of concern.

METHODS

The study was a descriptive temporal survey design with secondary ecological data: the whole-genome sequence (WGS) from the Global Initiative on Sharing Avian Influenza (GISAID) and COVID-19 data from the Palembang City Health Office website. Bioinformatics software was used to detect mutations.

RESULTS

Palembang submitted 43 whole genome sequences, 13 of which were Pangoline sequences classifications.

CONCLUSIONS

The two concern variations, Alpha and Delta, were associated with increased transmissions and decreased vaccination efficacy using temporal analysis. Regulations governing the relaxation of mobility restrictions should be based on high rates of testing and tracing, and universal vaccination programs should require that all received two doses of any vaccines as fast as possible.

Analysis of SARS-CoV-2 Genomes from West Java, Indonesia

West Java Health Laboratory (WJHL) is one of the many institutions in Indonesia that have sequenced SARS-CoV-2 genome. Although having submitted a large number of sequences since September 2020, however, these submitted data lack advanced analyses. Therefore, in this study, we analyze the variant distribution, hotspot mutation, and its impact on protein structure and function of SARS-CoV-2 from the collected samples from WJHL. As many as one hundred sixty-three SARS-CoV-2 genome sequences submitted by West Java Health Laboratory (WJHL), with collection dates between September 2020 and June 2021, were retrieved from GISAID. Subsequently, the frequency and distribution of non-synonymous mutations across different cities and regencies from these samples were analyzed. The effect of the most prevalent mutations from dominant variants on the stability of their corresponding proteins was examined. The samples mostly consisted of people of working-age, and were distributed between female and male equally. All of the sample sequences showed varying levels of diversity, especially samples from West Bandung which carried the highest diversity. Dominant variants are the VOC B.1.617.2 (Delta) variant, B.1.466.2 variant, and B.1.470 variant. The genomic regions with the highest number of mutations are the spike, NSP3, nucleocapsid, NSP12, and ORF3a protein. Mutation analysis showed that mutations in structural protein might increase the stability of the protein. Oppositely, mutations in non-structural protein might lead to a decrease in protein stability. However, further research to study the impact of mutations on the function of SARS-CoV-2 proteins are required.

Geo-clusters and socio-demographic profiles at village-level associated with COVID-19 incidence in the metropolitan city of Jakarta: An ecological study

The Special Capital Region of Jakarta is the epicentre of the transmission of COVID‐19 in Indonesia. However, much remains unknown about the spatial and temporal patterns of COVID‐19 incidence and related socio‐demographic factors explaining the variations of COVID‐19 incidence at local level. COVID‐19 cases at the village level of Jakarta from March 2020 to June 2021 were analyzed from the local public COVID‐19 dashboard. Global and local spatial clustering of COVID‐19 incidence was examined using the Moran's I and local Moran analysis. Socio‐demographic profiles of identified hotspots were elaborated. The association between village characteristics and COVID‐19 incidence was evaluated. The COVID‐19 incidence was significantly clustered based on the geographical village level (Moran's I = 0.174; p = .002). Seventeen COVID‐19 high‐risk clusters were found and dynamically shifted over the study period. The proportion of people aged 20–49 (incidence rate ratio [IRR] = 1.016; 95% confidence interval [CI]: 1.012–1.019), proportion of elderly (≥50 years) (IRR = 1.045; 95% CI = 1.041–1.050), number of households (IRR = 1.196; 95% CI = 1.193–1.200), access to metered water for washing, and the main occupation of the residents were village level socio‐demographic factors associated with the risk of COVID‐19. Targeted public health responses such as restriction, improved testing and contact tracing, and improved access to health services for those vulnerable populations are essential in areas with high‐risk COVID‐19.

Laboratory Readiness and Response for SARS-Cov-2 in Indonesia

The laboratory diagnosis of SARS-CoV-2 infection comprises the informational cornerstone in the effort to contain the infections. Therefore, the ability to leverage laboratories' capacity in diagnostic testing and to increase the number of people being tested are critical. This paper reviews the readiness of Indonesian laboratories during the early months of the pandemic. It discusses the success of cross-sectoral collaboration among previously siloed national and sub-national government institutions, international development agencies, and private sector stakeholders. This collaboration managed to scale-up the COVID-19 referral laboratory network from one Ministry of Health NIHRD laboratory in the capital to 685 laboratories across 34 provinces. However, this rapid growth within 12 months since the first Indonesian case was discovered remained insufficient to cater for the constantly surging testing demands within the world's fourth most populous country. Reflecting on how other countries built their current pandemic preparedness from past emergencies, this paper highlights challenges and opportunities in workforce shortage, logistic distribution, and complex administration that need to be addressed.

Global Temporal Patterns of Age Group and Sex Distributions of COVID-19

Since the beginning of 2020, COVID-19 has been the biggest public health crisis in the world. To help develop appropriate public health measures and deploy corresponding resources, many governments have been actively tracking COVID-19 in real time within their jurisdictions. However, one of the key unresolved issues is whether COVID-19 was distributed differently among different age groups and between the two sexes in the ongoing pandemic. The objectives of this study were to use publicly available data to investigate the relative distributions of COVID-19 cases, hospitalizations, and deaths among age groups and between the sexes throughout 2020; and to analyze temporal changes in the relative frequencies of COVID-19 for each age group and each sex. Fifteen countries reported age group and/or sex data of patients with COVID-19. Our analyses revealed that different age groups and sexes were distributed differently in COVID-19 cases, hospitalizations, and deaths. However, there were differences among countries in both their age group and sex distributions. Though there was no consistent temporal change across all countries for any age group or either sex in COVID-19 cases, hospitalizations, and deaths, several countries showed statistically significant patterns. We discuss the potential mechanisms for these observations, the limitations of this study, and the implications of our results on the management of this ongoing pandemic.

Correlation of Demographics, Healthcare Availability, and COVID-19 Outcome: Indonesian Ecological Study

Objective: To analyze the correlation between demographic and healthcare availability indicators with COVID-19 outcome among Indonesian provinces. Methods: We employed an ecological study design to study the correlation between demographics, healthcare availability, and COVID-19 indicators. Demographic and healthcare indicators were obtained from the Indonesian Health Profile of 2019 by the Ministry of Health while COVID-19 indicators were obtained from the Indonesian COVID-19 website in August 31st 2020. Non-parametric correlation and multivariate regression analyses were conducted with IBM SPSS 23.0. Results: We found the number of confirmed cases and case growth to be significantly correlated with demographic indicators, especially with distribution of age groups. Confirmed cases and case growth was significantly correlated (p < 0.05) with population density (correlation coefficient of 0.461 and 0.491) and proportion of young people (-0.377; -0.394). Incidence and incidence growth were correlated with ratios of GPs (0.426; 0.534), hospitals (0.376; 0.431), primary care clinics (0.423; 0.424), and hospital beds (0.472; 0.599) per capita. For mortality, case fatality rate (CFR) was correlated with population density (0.390) whereas mortality rate was correlated with ratio of hospital beds (0.387). Multivariate analyses found confirmed case independently associated with population density (β of 0.638) and demographic structure (-0.289). Case growth was independently associated with density (0.763). Incidence growth was independently associated with hospital bed ratio (0.486). Conclusion: Pre-existing inequality of healthcare availability correlates with current reported incidence and mortality rate of COVID-19. Lack of healthcare availability in some provinces may have resulted in artificially low numbers of cases being diagnosed, lower demands for COVID-19 tests, and eventually lower case-findings.