A steady trickle-down from metro districts and improving epidemic-parameters characterize the increasing COVID-19 cases in India

Background. By mid-September of 2020, the number of daily new infections in India have crossed 95,000. To facilitate an intuition for the spatio-temporal development of the pandemic and to help resource deployment planning, we analyze and describe how the disease burden almost-predictably shifted from large metropolitan districts to sub-urban districts. Methods. We gathered the publicly available granular data from 186 different districts (equivalent of counties) on their COVID-19 infections and deaths during the 15 April to 31 August 2020 period. These districts presented an active case burden of 559,566 and a cumulative 2,715,656 infections as of August 31. The epidemiological data of these districts was fit to a susceptible-asymptomatic-infected-recovered-dead (SAIRD) model and the underlying epidemic parameters for each of these districts during the course of 4 months was estimated. We validated these parameters against known epidemiological characteristic distributions and analyzed them to understand their changes in space-time during the pandemic. Findings. The center of the burden of the current-active infections which on May 15 was in the large metro districts with most international access shifted continuously and smoothly shifted towards districts which could be accessed by domestic airports and by trains. A linear trend-analysis showed a continuous improvement in most epidemic parameters consistently across the districts with four categories of accessibility from an international travel perspective - large metro, metro, urban and sub-urban districts. The reproduction numbers improved from 1.77±0.58 on May 15 to 1.07± 0.13 on August 31 in large metro districts (p-Value of trend 0.0001053); and from 1.58±0.39 on May 15 to 0.94±0.11 on August 31 in sub-urban districts (p-Value of trend 0.0067). The recovery rate per infected person per day improved from 0.0581±0.009 on May 15 to 0.091±0.010 on August 31 in large metro districts (p-Value of trend 0.26.10^{-12}); and from 0.059±0.011 on May 15 to 0.100±0.010 on August 31 in sub-urban districts (p-Value of trend 0.12.10{-16}). The death rate of symptomatic individuals which includes the case-fatality-rate as well as the time from symptoms to death, consistently decreased from 0.0025±0.0014 on May 15 to 0.0013±0.0003 on August 31 in large metro districts (p-Value of trend 0.0010); and from 0.0018±0.0008 on May 15 to 0.0014±0.0003 on August 31 in sub-urban districts (p-Value of trend 0.2789. Interpretation. As the daily infections continue to rise at a national level, it is important to notice a `local-flattening' in larger metro districts, and a shift of the pandemic-burden towards smaller sized districts in a clear hierarchical fashion of accessibility from an international travel perspective. The pandemic burden shifting towards remotely accessible regions, with possibly lesser health care facilities, is a call for attention to the re-organization of resources.

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The micro-hotspots of cholera in Kano State, Nigeria, 2010-2019—analysis of patient characteristics, Spatio-temporal patterns and contextual determinants at the ward level

10.1101/2021.08.20.21262313 ◽

2021 ◽

Author(s):

Moise Chi Ngwa ◽

Chikwe Ihekweazu ◽

Tochi Joy Okwor ◽

Sebastian Yennan ◽

Nanpring Williams ◽

...

Keyword(s):

Urban Areas ◽

Task Force ◽

Case Fatality ◽

The State ◽

Rural Setting ◽

P Value ◽

Care Seeking ◽

Rural Settings ◽

Ward Level ◽

Spatio Temporal

AbstractCholera is endemic in Nigeria, and Kano State reports outbreaks yearly with a case fatality rate (CFR) of 3.3% from 2010 to 2019. The lack of data at ward level has enabled the disease to evade focused interventions. The goal of this study was to describe the geographic distributions, care-seeking behaviors, Spatio-temporal cluster patterns of the micro-hotspots (hotspots wards) linked with suspected and confirmed cases and deaths of cholera in Kano State.Suspected and confirmed cholera morbidity and mortality at the ward level from 2010-2019 were acquired from the Nigeria Centre for Disease Control. Population and waterbody data were obtained from the Nigeria Expanded Program on Immunization and online, respectively. Data analysis used SaTScan and methods recommended by the Global Task Force on Cholera Control.During these ten years, 18,483 suspected and confirmed cases (617 deaths) were reported with 67.7% of the cases and 72% of the deaths from rural wards. The ages of the cases ranged from 1 month to 100 years with a distribution skewed to the older years. CFRs were statistically higher in the <5-year olds compared to those >14 years (p-value = 0.0005). For 2010-2019, gender was statistically associated with cholera outcome (survived/died) (p-value = 0.0006), and women in the rural setting disproportionately died from cholera than women in the urban area (p-value = 0.003). Cholera severity, as measured by hospitalization and death, was higher in the urban (77.4%) compared with the rural (53.4%) setting with the highest severity (84.7%) registered among those >14 years. Rapid Diagnostic Tests (RDT) were performed in 1.3% (249) samples of all suspected cases and ranged from 0.7% among the 5-14 year-olds in the rural to 3.5 % among the < 5-year-olds in the urban areas. Of the stool samples collected, 62.7% tested positive for V. cholerae using RDT. The positivity rate was least in the urban setting amongst the <5 years (41.2%) while care-seeking-behavior ranged from 52.1% in the urban to 82.7% in the rural settings. Seasonal patterns of disease often differed between urban and rural settings with outbreaks occurring in both the dry and rainy seasons, but with more intense transmission occurring during the rainy season from week 22 (early June) to week 40 (late September). A Spatio-temporal clustering analysis detected 168 micro-hotspots out of 404 wards, with a population of 4,876,254, having a significantly higher risk (relative risk 1.01-18.73) compared to the State as a whole. While 79 micro-hotspots with a population of 2,119,974 had a RR ≥ 2. The micro-hotspots tended to cluster around waterbodies. SaTScan and GTFCC methods generally agreed in micro-hotspots detection.This study shows the epidemiology of cholera in Kano State differs between urban and rural settings and that hotspot maps at the ward level, not hotpots maps at the Local Government Area level, are best suited for targeting interventions including vaccines. Appropriate studies are needed to further delineate the urban and rural divide of outbreaks but targeting interventions to the identified high-priority micro-hotspots will facilitate cholera elimination from the state.Author summaryCholera is endemic in Nigeria since 1970, and Kano State reports outbreaks almost every year. From 2010-2019, Kano State reported 18,483 cases and 617 deaths, for a case fatality rate of 3.3%. Focusing interventions at the Local Government Area instead of the ward (local) level contributed to the continuous threat from cholera in Kano State. When we divided the state into its two geographic areas (urban and rural), there were very different epidemiology as well as Spatio-temporal patterns of clustering of wards with elevated relative risk (micro-hotspots). Nearly two-thirds of the cases and deaths were reported from rural wards. The ages of the cases ranged from 1 month to 100 years with case fatality ratios higher in the <5-years olds compared to those >14 years (p-value = 0.0005). Women in the rural area not only had more cases but also were more likely to die from cholera than women in the urban area (p-value = 0.003). The hospitalization rate was higher in the urban than rural setting whereas care-seeking behavior was higher in rural than urban areas. Rapid Diagnostic Tests to confirm cholera was very low overall. Seasonal patterns of disease differed between urban and rural areas with outbreaks occurring in both the dry and rainy seasons, but with more cases from June to September, during the rainy season. A population of 4,876,254 live in the 168 micro-hotspots in which cholera risks were 1.01 to 18.73 times higher compared to the State as a whole. Following the Global Task Force on Cholera Control recommendations, interventions should focus on these identified micro-hotspots for cholera elimination from Kano State.

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Impact of COVID-19 Pandemic on Refugees, Migrants and Asylum Seekers Living in Camps and Reception and Identification Centers in Greece in the Pre-Vaccination Period, February 2020 to May 2021. Summary of Epidemiological Findings

10.21203/rs.3.rs-911182/v1 ◽

2021 ◽

Author(s):

Spiros Sapounas ◽

Konstantinos Mitrou ◽

Alexandros Georgios Asimakopoulos ◽

Garyfallia Antoniou ◽

Ioanna Papari ◽

...

Keyword(s):

General Population ◽

Asylum Seekers ◽

Case Fatality Rate ◽

Clinical Manifestations ◽

Case Fatality ◽

Population Data ◽

Epidemiological Data ◽

P Value ◽

Fatality Rate ◽

Notification Rate

Abstract Background: Protection of refugees, migrants, and asylum seekers living in open hosting camps (HCs) and reception and identification centers (RICs) has been a priority since the beginning of the COVID-19 pandemic. We present the epidemiological data of COVID-19 infection in HCs/RICs in Greece from February 2020 to May 2021, before the initiation of the onsite vaccinations.Methods: Case confirmation was performed by rapid antigenic test and/or RT-PCR. Data were retrieved from the National COVID-19 registry. The notification rate by type of accommodation facility, by sex and ethnicity and the mean age of cases, were calculated for HCs, RICs and general population. Data on clinical manifestations, and disease severity (admissions to intensive care unit (ICU) / case fatality rate) were analysed.Results: Of the 397,497 recorded domestic COVID-19 infection cases, 2,609 (0.7%) regarded HCs/RICs; of them 1,566 (60%) were identified in 27 HCs and 1,043 (40%) in six RICs. The notification rate was 542 and 380 cases per 10,000 population in HCs/RICs and the general population, respectively (p-value<0.001).Up to February 2021 the occurrence of cases in HCs/RICs did not follow the occurrence of cases in the general population. After March 2021 the course of the outbreak in HCs/RICs and the general population was similar.The median age of cases in HCs/RICs and the general population was 27 (range:0-81) and 44 (range:0-106), respectively (p<0.001). Twenty-four different ethnicities were reported among migrant cases; 51% were from Afghanistan, 13% from Syria, 6% from Kongo and 5% from Somalia.Overall, 48% and 80% of cases, respectively in HCs/RICs and the general population were symptomatic (p<0.001). Five (0.2%) cases in HCs/RICs were admitted to the ICU compared to 10,426 cases (3.0%) in the general population (p-value <0.001). Case fatality rate was 3% in the general population and 0.08% in HCs/RICs (p-value <0.001).Conclusion: Recorded COVID-19 infections were less severe in migrants living at HCs/RICs than the general population, however, the number of identified cases was high and measures for the prevention of transmission should be strengthened.

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Effect of preventive actions and health care factors in controlling the outbreaks of COVID-19 pandemic

10.1101/2020.05.09.20096255 ◽

2020 ◽

Cited By ~ 1

Author(s):

Faruq Abdulla ◽

Zulkar Nain ◽

Md. Karimuzzaman ◽

Md. Moyazzem Hossain ◽

Utpal Kumar Adhikari ◽

...

Keyword(s):

Health Care ◽

Case Fatality ◽

Medical Personnel ◽

Health Care Facilities ◽

Control Measures ◽

P Value ◽

Preventive Actions ◽

Care Facilities ◽

Hospital Beds ◽

Short Time

With the insurgence of the COVID-19 pandemic, a large number of people died in the past several months, and the situation is ongoing with increasing health, social and economic panic and vulnerability. Due to the lack of drugs and prophylaxis against COVID-19, most of the countries are now relying on maintaining social distance as preventative actions. However, this social distancing can create global socio-economic crisis and psychological disorders. Therefore, these control measures need to have an assessment to evaluate their value in containing the situation. In this study, we analyzed the outcome of COVID-19 in response to different control measures, health care facilities, and prevalent diseases. Based on our findings, the number of COVID-19 deaths found to be reduced with increased medical personnel and hospital beds. We found 0.23, 0.16, and 0.21 as the measurement of significant non-linear relationship between COVID-19 case fatality and number of physicians (p-value ≤ 7.1*10-6), nurses and midwives (p-value ≤ 4.6*10-3), and hospital beds (p-value ≤ 1.9*10-2). Importantly, we observed a significant correlation between the reduction of COVID-19 cases and the earliness of preventive initiation. As a result, enhancing health care facilities as well as imposing the control measures in a short time could be valuable to prevent the currently raging COVID-19 pandemic. The apathy of taking nation-wide immediate precaution measure has identified as one of the critical reasons to make the circumstances worst. Notably, countries including Gambia, Nicaragua, Burundi, Namibia, and Nepal have marked in a state of danger. Interestingly, no association between the comorbidities and severity of COVID-19 was found except for few diseases including cancer, which warranted further investigation at the pathobiological level. We believe that this study could be useful in developing a control strategy in COVID-19 as well as future pandemics.

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Surface Web Merits for SARS-CoV-2 Pandemic in Iraq

Journal of the Faculty of Medicine Baghdad ◽

10.32007/jfacmedbagdad.6241795 ◽

2021 ◽

Vol 62 (4) ◽

pp. 117-127

Author(s):

Ahmed Al-Imam ◽

Marek A. Motyka ◽

Hend J. Al-Doori

Keyword(s):

Machine Learning ◽

Temporal Trends ◽

Epidemiological Data ◽

P Value ◽

Search Term ◽

Ministry Of Health ◽

Multivariate Tests ◽

Search Terms ◽

Epidemiology Data ◽

Spatio Temporal

Background: Data on SARS-CoV-2 from developing countries is not entirely accurate, demanding incorporating digital epidemiology data on the pandemic. Objectives: To reconcile non-Bayesian models and artificial intelligence connected with digital and classical (non-digital) epidemiological data on SARS-CoV-2 pandemic in Iraq. Results: Baghdad and Sulaymaniyah represented statistical outliers in connection with daily cases and recoveries, and daily deaths, respectively. Multivariate tests and neural networks detected a predictor effect of deaths, recoveries, and daily cases on web searches concerning two search terms, "كورونا" and "Coronavirus" (Pillai's Trace value=1, F=1106915.624, Hypothesis df=3, Error df=12, p-value<0.001, Partial Eta Squared=1). Using hierarchical clustering, we identified distinctive aggregates involving the Iraqi capital, Kurdistan region, and the south of Iraq. Three search terms were most prevalent among Iraqi web users, including "كورونا", "كوفيد-19", and "Coronavirus". Significant bivariate correlations were all positive except for those involving the search term "لقاح كورونا". Al-Muthanna governorate residents were least interested in data on SARS-CoV-2 vaccines.Methods: Our study design is longitudinal, for the period from 24 February 2020 to 25 September 2020. We retrieved data from the Iraqi Ministry of Health on the daily cases, recoveries, and deaths from SARS-CoV-2, and incorporated collateral data from Google Trends using five search terms, "Coronavirus", "كورونا", "COVID-19", "كوفيد-19", and "لقاح كورونا". The search terms "كورونا", "كوفيد-19", and "لقاح كورونا" represent the Arabic translations for "Coronavirus", "COVID-19", and "COVID-19 Vaccine". We implemented multivariate tests and machine learning to scrutinize the spatio-temporal trends of the pandemic in Iraq and interpret the causality influencing Iraqis to seek digital knowledge, via the web, on SARS-CoV-2. Conclusion: Our analyses were triumphant in syncretizing non-Bayesian and machine learning models, using two forms of epidemiology data on the pandemic in Iraq. We opine that the current study is exquisite and precious for decision-makers at the Iraqi Ministry of Health.

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A partisan pandemic: state government public health policies to combat COVID-19 in Brazil

BMJ Global Health ◽

10.1136/bmjgh-2021-005223 ◽

2021 ◽

Vol 6 (6) ◽

pp. e005223

Author(s):

Michael Touchton ◽

Felicia Marie Knaul ◽

Héctor Arreola-Ornelas ◽

Thalia Porteny ◽

Mariano Sánchez ◽

...

Keyword(s):

Public Space ◽

State Government ◽

Public Transportation ◽

National Level ◽

International Travel ◽

School Closure ◽

Population Mobility ◽

Mato Grosso ◽

First Case ◽

National Response

IntroductionTo present an analysis of the Brazilian health system and subnational (state) variation in response to the COVID-19 pandemic, based on 10 non-pharmaceutical interventions (NPIs).Materials and methodsWe collected daily information on implementation of 10 NPI designed to inform the public of health risks and promote distancing and mask use at the national level for eight countries across the Americas. We then analyse the adoption of the 10 policies across Brazil’s 27 states over time, individually and using a composite index. We draw on this index to assess the timeliness and rigour of NPI implementation across the country, from the date of the first case, 26 February 2020. We also compile Google data on population mobility by state to describe changes in mobility throughout the COVID-19 pandemic.ResultsBrazil’s national NPI response was the least stringent among countries analysed. In the absence of a unified federal response to the pandemic, Brazilian state policy implementation was neither homogenous nor synchronised. The median NPI was no stay-at-home order, a recommendation to wear masks in public space but not a requirement, a full school closure and partial restrictions on businesses, public transportation, intrastate travel, interstate travel and international travel. These restrictions were implemented 45 days after the first case in each state, on average. Rondônia implemented the earliest and most rigorous policies, with school closures, business closures, information campaigns and restrictions on movement 24 days after the first case; Mato Grosso do Sul had the fewest, least stringent restrictions on movement, business operations and no mask recommendation.ConclusionsThe study identifies wide variation in national-level NPI responses to the COVID-19 pandemic. Our focus on Brazil identifies subsequent variability in how and when states implemented NPI to contain COVID-19. States’ NPIs and their scores on the composite policy index both align with the governors’ political affiliations: opposition governors implemented earlier, more stringent sanitary measures than those supporting the Bolsonaro administration. A strong, unified national response to a pandemic is essential for keeping the population safe and disease-free, both at the outset of an outbreak and as communities begin to reopen. This national response should be aligned with state and municipal implementation of NPI, which we show is not the case in Brazil.

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Identification of Polyomaviruses in Skin Cancers

Intervirology ◽

10.1159/000513544 ◽

2021 ◽

pp. 96-102

Author(s):

Pedro V.A. Costa ◽

Patricia S. Ishiy ◽

Paulo R.P. Urbano ◽

Camila M. Romano ◽

Stephen K. Tyring ◽

...

Keyword(s):

Cell Carcinoma ◽

Normal Skin ◽

Dermatofibrosarcoma Protuberans ◽

Epidemiological Data ◽

Skin Carcinogenesis ◽

P Value ◽

Merkel Cell ◽

Cross Sectional ◽

Skin Tumours ◽

Skin Tumour

Background: Polyomaviruses (PyVs) were initially described in animals. They have also been detected in humans with some evidence that could play a role in skin carcinogenesis. Objectives: This study aimed to verify the presence of PyVs in different skin tumour samples and to make clinical correlations with patients’ epidemiological data from Clinics Hospital of Medical School of University of São Paulo, Brazil. Methods: This is a cross-sectional study. A random selection was performed of 120 patients with histopathological exams of different cutaneous neoplasms equally divided into 6 groups and 20 patients with normal skin. The available skin specimens were analysed with 2 different techniques of PCR (conventional and real time) for detection of PyV DNA. Concomitantly, retrospective analysis of the respective medical records for the collection of epidemiological data was done. Analyses suitable for categorical data were used to compare the proportion of patients in each group. Results: PyV DNA was found in 25.69% of the samples: 15% in basal cell carcinoma group, 15% in squamous cell carcinoma, 28.57% in melanoma, 15% in dermatofibrosarcoma protuberans, 13.33% in Kaposi sarcoma, 65% in Merkel cell carcinoma (MCC), and none in normal skin. Merkel cell PyV detection was statistically significant in MCC patients (p value <0.01), but no correlations were found between PyVs and others skin tumours. Conclusion: This study demonstrated the presence of PyVs in different skin tumours; however, no association of any PyVs found in any skin tumour with epidemiological data could be shown. Further studies are still needed to elucidate the mechanisms of PyVs in skin carcinogenesis.

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Population-Predicted MHC Class II Epitope Presentation of SARS-CoV-2 Structural Proteins Correlates to the Case Fatality Rates of COVID-19 in Different Countries

International Journal of Molecular Sciences ◽

10.3390/ijms22052630 ◽

2021 ◽

Vol 22 (5) ◽

pp. 2630

Author(s):

Chunguang Liang ◽

Elena Bencurova ◽

Eric Psota ◽

Priya Neurgaonkar ◽

Martina Prelog ◽

...

Keyword(s):

Mhc Class Ii ◽

Case Fatality Rate ◽

Case Fatality ◽

Class Ii ◽

Viral Envelope ◽

Structural Proteins ◽

P Value ◽

Fatality Rate ◽

Different Populations ◽

Infection Spread

We observed substantial differences in predicted Major Histocompatibility Complex II (MHCII) epitope presentation of SARS-CoV-2 proteins for different populations but only minor differences in predicted MHCI epitope presentation. A comparison of this predicted epitope MHC-coverage revealed for the early phase of infection spread (till day 15 after reaching 128 observed infection cases) highly significant negative correlations with the case fatality rate. Specifically, this was observed in different populations for MHC class II presentation of the viral spike protein (p-value: 0.0733 for linear regression), the envelope protein (p-value: 0.023), and the membrane protein (p-value: 0.00053), indicating that the high case fatality rates of COVID-19 observed in some countries seem to be related with poor MHC class II presentation and hence weak adaptive immune response against these viral envelope proteins. Our results highlight the general importance of the SARS-CoV-2 structural proteins in immunological control in early infection spread looking at a global census in various countries and taking case fatality rate into account. Other factors such as health system and control measures become more important after the early spread. Our study should encourage further studies on MHCII alleles as potential risk factors in COVID-19 including assessment of local populations and specific allele distributions.

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The Role of Spatio-Temporal Information to Govern the COVID-19 Pandemic: A European Perspective

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10030166 ◽

2021 ◽

Vol 10 (3) ◽

pp. 166

Author(s):

Hartmut Müller ◽

Marije Louwsma

Keyword(s):

European Union ◽

Spatial Distribution ◽

Spatial Information ◽

National Level ◽

Temporal Information ◽

The European Union ◽

Member States ◽

Heavy Burden ◽

Spatio Temporal

The Covid-19 pandemic put a heavy burden on member states in the European Union. To govern the pandemic, having access to reliable geo-information is key for monitoring the spatial distribution of the outbreak over time. This study aims to analyze the role of spatio-temporal information in governing the pandemic in the European Union and its member states. The European Nomenclature of Territorial Units for Statistics (NUTS) system and selected national dashboards from member states were assessed to analyze which spatio-temporal information was used, how the information was visualized and whether this changed over the course of the pandemic. Initially, member states focused on their own jurisdiction by creating national dashboards to monitor the pandemic. Information between member states was not aligned. Producing reliable data and timeliness reporting was problematic, just like selecting indictors to monitor the spatial distribution and intensity of the outbreak. Over the course of the pandemic, with more knowledge about the virus and its characteristics, interventions of member states to govern the outbreak were better aligned at the European level. However, further integration and alignment of public health data, statistical data and spatio-temporal data could provide even better information for governments and actors involved in managing the outbreak, both at national and supra-national level. The Infrastructure for Spatial Information in Europe (INSPIRE) initiative and the NUTS system provide a framework to guide future integration and extension of existing systems.

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Beyond national indicators: adapting the Demographic and Health Surveys’ sampling strategies and questions to better inform subnational malaria intervention policy

Malaria Journal ◽

10.1186/s12936-021-03646-w ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Ifeoma D. Ozodiegwu ◽

Monique Ambrose ◽

Katherine E. Battle ◽

Caitlin Bever ◽

Ousmane Diallo ◽

...

Keyword(s):

Health Surveys ◽

Survey Design ◽

National Level ◽

National Policy ◽

Sampling Strategy ◽

Epidemiological Data ◽

Malaria Prevalence ◽

Demographic And Health Surveys ◽

Malaria Indicator Survey ◽

Narrow Scope

AbstractIn malaria-endemic countries, prioritizing intervention deployment to areas that need the most attention is crucial to ensure continued progress. Global and national policy makers increasingly rely on epidemiological data and mathematical modelling to help optimize health decisions at the sub-national level. The Demographic and Health Surveys (DHS) Program is a critical data source for understanding subnational malaria prevalence and intervention coverage, which are used for parameterizing country-specific models of malaria transmission. However, data to estimate indicators at finer resolutions are limited, and surveys questions have a narrow scope. Examples from the Nigeria DHS are used to highlight gaps in the current survey design. Proposals are then made for additional questions and expansions to the DHS and Malaria Indicator Survey sampling strategy that would advance the data analyses and modelled estimates that inform national policy recommendations. Collaboration between the DHS Program, national malaria control programmes, the malaria modelling community, and funders is needed to address the highlighted data challenges.

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The COVID-19 Pandemic Situation in Malaysia: Lessons Learned from the Perspective of Population Density

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18126566 ◽

2021 ◽

Vol 18 (12) ◽

pp. 6566

Author(s):

Siew Bee Aw ◽

Bor Tsong Teh ◽

Gabriel Hoh Teck Ling ◽

Pau Chung Leng ◽

Weng Howe Chan ◽

...

Keyword(s):

Population Density ◽

Pearson Correlation ◽

Strong Relationship ◽

Lessons Learned ◽

P Value ◽

Population Census ◽

Infection Rates ◽

Health Official ◽

Contagious Diseases ◽

Spatio Temporal

This paper attempts to ascertain the impacts of population density on the spread and severity of COVID-19 in Malaysia. Besides describing the spatio-temporal contagion risk of the virus, ultimately, it seeks to test the hypothesis that higher population density results in exacerbated COVID-19 virulence in the community. The population density of 143 districts in Malaysia, as per data from Malaysia’s 2010 population census, was plotted against cumulative COVID-19 cases and infection rates of COVID-19 cases, which were obtained from Malaysia’s Ministry of Health official website. The data of these three variables were collected between 19 January 2020 and 31 December 2020. Based on the observations, districts that have high population densities and are highly inter-connected with neighbouring districts, whether geographically, socio-economically, or infrastructurally, tend to experience spikes in COVID-19 cases within weeks of each other. Using a parametric approach of the Pearson correlation, population density was found to have a moderately strong relationship to cumulative COVID-19 cases (p-value of 0.000 and R2 of 0.415) and a weak relationship to COVID-19 infection rates (p-value of 0.005 and R2 of 0.047). Consequently, we provide several non-pharmaceutical lessons, including urban planning strategies, as passive containment measures that may better support disease interventions against future contagious diseases.

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