On March 11, 2023, Malaysia recorded 223 new confirmed cases of COVID-19, reflecting an increase from more than 160 cases on March 5, 2023. Malaysia is still expecting a rise due to the highly contagious variant of Omicron.

Malaysia is currently one out of more than 200 countries and territories battling with the novel coronavirus. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

As of November 4, 2023, Malaysia recorded over 5.1 million confirmed cases of COVID-19 and around 37.1 thousand deaths from the virus. Currently, Malaysia has successfully vaccinated over 80 percent of its population and is experiencing a decrease in cases, although the country still expecting a rise due to the highly contagious variant of Omicron.

Malaysia is currently one out of more than 200 countries and territories battling with the novel coronavirus. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Clinical data from patients hospitalised with COVID19 in Malaysia, shared as a part of the ISARIC Clinical Characterisation Group collaboration.

In past 24 hours, Malaysia, Asia had N/A new cases, N/A deaths and N/A recoveries.

Malaysia recorded 5079436 Coronavirus Cases since the epidemic began, according to the World Health Organization (WHO). In addition, Malaysia reported 37028 Coronavirus Deaths. This dataset includes a chart with historical data for Malaysia Coronavirus Cases.

On March 11, 2023, Malaysia had approximately five million confirmed cases of COVID-19. Over the past week, Malaysia has seen a decrease in the number of new cases each day, but still expects an increase due to the highly-contagious Omicron variant.

Malaysia is currently one out of more than 200 countries and territories battling with the novel coronavirus. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

This repository collects Singapore and Malaysia COVID-19 data from multiple data sources such as zaobao.sg and the Ministry of Health (MOH). The repository is updated multiple times per day. From June 1, 2020, Zaobao stopped updating the data so only Singapore MOH data are still daily updated. This database contains, updated until June 1st: detailed information about each case (demography data, date of onset, hospitalization, date of report, travel information, date of discharge or death), important action taken by the Singapore government, records of activities and status of each case, aggregated data by day, the daily numbers of suspect cases, close contacts, number of cases, deaths and their status. The repository contains also : the daily press release from MOH (until end of March 2023), the daily press release from the MOH of Malaysia, and the WHO situation reports. The repository contains information in multiple language.

Dataset

This dataset was created by Khairul Hafiz

Released under Data files © Original Authors

Contents

As of November 4, 2023, Malaysian states of Putrajaya and Kuala Lumpur had respectively around 36.1 and 30.6 coronavirus (COVID-19) confirmed cases per 100,000 people, the highest in the country. Malaysia is experiencing a decrease in cases, although the country still expecting a rise due to the highly contagious variant of Omicron.

Malaysia is currently one out of more than 200 countries and territories battling with the novel coronavirus. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Dataset of knowledge, attitudes and practices towards COVID-19 among Malaysian

The number of COVID-19 vaccination doses administered per 100 people in Malaysia rose to 214 as of Oct 27 2023. This dataset includes a chart with historical data for Malaysia Coronavirus Vaccination Rate.

The Coronavirus (SARS-CoV-2) outbreak, dubbed COVID-19, is first and foremost a human tragedy, affecting millions of people globally. The contagious Coronavirus, which broke out at the close of 2019, has led to a medical emergency across the world, with the World Health Organization officially declaring the novel Coronavirus a pandemic on March 11, 2020. Read More

The objective of this study is to understand the epidemiology of COVID-19 in Sabah from March 2020 through October 2021 and to determine the factors associated with COVID-19 severity. The data used in this study were provided by the Surveillance Unit, Sabah State Health Department, Ministry of Health Malaysia. Individuals aged ≤5 years old and ≥ 65 years old (AOR=1.87, 95% CI: 1.77–1.99), non-citizens of Malaysia (AOR=1.46, 95% CI: 1.30–1.64), male gender (AOR=1.06, 95% CI: 1.01–1.12), native Sabahan (AOR=1.30, 95% CI: 1.19–1.42), presence of symptoms of COVID-19 infection (AOR=23.33, 95% CI: 20.75-26.23), presence of comorbidity (AOR=1.80, 95% CI: 1.67-1.94), high exposure risk of COVID-19 infection (AOR=0.44, 95% CI: 0.28-0.71), and incomplete COVID-19 vaccination (AOR=8.53, 95% CI: 7.35-9.89) were statistically significantly associated with developing severe COVID-19 infection.

Abstract

The World Bank has launched a fast-deploying high-frequency phone-based survey of households to generate near real time insights into the socio-economic impact of COVID-19 on households which hence to be used to support evidence-based policy responses to the crisis. At a time when conventional modes of data collection are not feasible, this phone-based rapid data collection method offers a way to gather granular information on the transmission mechanisms of the crisis on the populations, to identify gaps in policy responses, and to generate insights to inform scaling up or redirection of resources as the crisis unfolds.

Geographic coverage

National

Analysis unit

Individual, Household-level

Sampling procedure

A mobile frame was generated via random digit dialing (RDD), based on the National Numbering Plans from the Malaysian Communications and Multimedia Commission (MCMC). All possible subscriber combinations were generated in DRUID (D Force Sampling's Reactive User Interface Database), an SQL database interface which houses the complete sampling frame. From this database, complete random telephone numbers were sampled. For Round 1, a sample of 33,894 phone numbers were drawn (without replacement within the survey wave) from a total of 102,780,000 possible mobile numbers from more than 18 mobile providers in the sampling frame, which were not stratified. Once the sample was drawn in the form of replicates (subsamples) of n = 10.000, the numbers were filtered by D-Force Sampling using an auto-dialer to determine each numbers' working status. All numbers that yield a working call disposition for at least one of the two filtering attempts were then passed to the CATI center human interviewing team. Mobile devices were assumed to be personal, and therefore the person who answered the call was the selected respondent. Screening questions were used to ensure that the respondent was at least 18 years old and within the capacity of either contributing, making or with knowledge of household finances. Respondents who had participated in Round 1 were sampled for Round 2. Fresh respondents were introduced in Round 3 in addition to panel respondents from Round 2; fresh respondents in Round 3 were selected using the same procedure for sampling respondents in Round 1.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The questionnaire is available in three languages, including English, Bahasa Melayu, and Mandarin Chinese. It can be downloaded from the Downloads section.

Response rate

In Round 1, the survey successfully interviewed 2,210 individuals out of 33,894 sampled phone numbers. In Round 2, the survey successfully re-interviewed 1,047 individuals, recording a 47% response rate. In Round 3, the survey successfully re-interviewed 667 respondents who had been previously interviewed in Round 2, recording a 64% response rate. The panel respondents in Round 3 were added with 446 fresh respondents.

Sampling error estimates

In Round 1, assuming a simple random sample, with p=0.5 and n=2,210 at the 95% CI level, yields a margin of sampling error (MOE) of 2.09 percentage points. Incorporating the design effect into this estimate yields a margin of sampling error of 2.65% percentage points.

In Round 2, the complete weight was for the entire sample adjusted to the 2021 population estimates from DOSM’s annual intercensal population projections. Assuming a simple random sample with p=0.5 and n=1,047 at the 95% CI level, yields a margin of sampling error (MOE) of 3.803 percentage points. Incorporating the design effect into this estimate yields a margin of sampling error of 3.54 percentage points.

Among both fresh and panel samples in Round 3, assuming a simple random sample, with p=0.5 and n=1,113 at the 95% CI level yields a margin of sampling error (MOE) of 2.94 percentage points. Incorporating the design effect into this estimate yields a margin of sampling error of 3.34 percentage points.

Among panel samples in Round 3, with p=0.5 and n=667 at the 95% CI level yields a margin of sampling error (MOE) of 3.80 percentage points. Incorporating the design effect into this estimate yields a margin of sampling error of 4.16 percentage points.

We aim to explore the impact of the COVID-19 pandemic on psychological stress and well-being of primary healthcare workers (HCWs) in Malaysia.

This Project Tycho dataset includes a CSV file with COVID-19 data reported in MALAYSIA: 2019-12-30 - 2021-07-31. It contains counts of cases and deaths. Data for this Project Tycho dataset comes from: "COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University", "European Centre for Disease Prevention and Control Website", "World Health Organization COVID-19 Dashboard". The data have been pre-processed into the standard Project Tycho data format v1.1.

As of July 13, 2022, 67 percent of Malaysian respondents stated that they had been avoiding public places during the COVID-19 outbreak, up from 40 percent on Feb 24, 2020. Malaysia is currently experiencing a decrease in the number of confirmed daily cases of COVID-19 infections, although the country still expecting a rise due to the highly contagious variant of Omicron.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Countries around the world are gearing for the transition of the coronavirus disease 2019 (COVID-19) from pandemic to endemic phase but the emergence of new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants could lead to a prolonged pandemic. SARS-CoV-2 has continued to evolve as it optimizes its adaptation to the human host and the successive waves of COVID-19 have been linked to the explosion of particular variant of concern. As the genetic diversity and epidemiological landscape of SARS-CoV-2 differ from country to country, this study aims to provide insights into the variants that are circulating in Malaysia. Whole genome sequencing was performed for 204 SARS-CoV-2 from COVID-19 cases and an additional 18,667 SARS-CoV-2 genome sequences were retrieved from the GISAID EpiCoV database for clade, lineage and genetic variation analyses. Complete genome sequences with high coverage were then used for phylogeny investigation and the resulting phylogenetic tree was constructed from 8,716 sequences. We found that the different waves of COVID-19 in Malaysia were dominated by different clades with the L and O clade for first and second wave, respectively, whereas the progressive replacement by G, GH, and GK of the GRA clade were observed in the subsequence waves. Continuous monitoring of the genetic diversity of SARS-CoV-2 is important to identify the emergence and dominance of new variant in different locality so that the appropriate countermeasures can be taken to effectively contain the spread of SARS-CoV-2.

Malaysia Central Govt COVID-19 Fund: Quarterly data was reported at 0.000 MYR mn in Dec 2024. This stayed constant from the previous number of 0.000 MYR mn for Sep 2024. Malaysia Central Govt COVID-19 Fund: Quarterly data is updated quarterly, averaging 0.000 MYR mn from Mar 1996 (Median) to Dec 2024, with 116 observations. The data reached an all-time high of 22,147.000 MYR mn in Jun 2020 and a record low of 0.000 MYR mn in Dec 2024. Malaysia Central Govt COVID-19 Fund: Quarterly data remains active status in CEIC and is reported by Bank Negara Malaysia. The data is categorized under Global Database’s Malaysia – Table MY.F001: Central Government Finance.

This data set contains data on Malaysians’ health status, internet and social media usage, mental health and protective behaviors during the COVID-19 Pandemic.