According to preliminary data between January and September 2023, 0.5 percent of deaths in the Philippines were identified as caused by the COVID-19 virus. COVID-related deaths peaked in 2021 with a share of 9.7 percent.

Philippines recorded 66453 Coronavirus Deaths since the epidemic began, according to the World Health Organization (WHO). In addition, Philippines reported 4115202 Coronavirus Cases. This dataset includes a chart with historical data for Philippines Coronavirus Deaths.

As of May 3, 2023, approximately 4.1 million people had been confirmed as infected with the COVID-19 virus in the Philippines. Of those, over four million had recovered and around 66.4 thousand died.

Vaccination rollout in the Philippines
The government’s vaccination drives successfully inoculated over 71 million Filipinos, surpassing the initial target of 70 million. This represented about 77 percent of the total eligible population to receive the vaccine. As of June 2022, the National Capital Region accounted for the highest share of the population that have been fully vaccinated from the virus, followed by Region 4-A.

Hybrid shopping behavior Lockdown restrictions across the country forced consumers to turn to e-commerce channels and digital payment systems to prevent themselves from contracting the virus. A survey revealed that about 46 percent of respondents in the Philippines were first social media shoppers in 2021.

According to preliminary data between January and September 2023, just 0.1 percent of deaths in the Philippines were reported as unidentified COVID-19 related. Deaths caused by unidentified COVID-19 virus peaked in 2021 at 4.1 percent.

As of April 13, 2024, India had the highest number of confirmed deaths due to the outbreak of the novel coronavirus in the Asia-Pacific region, with over 533 thousand deaths. Comparatively, Indonesia, which had the second highest number of coronavirus deaths in the Asia-Pacific region, recorded approximately 162 thousand COVID-19 related deaths as of April 13, 2024. Contrastingly, Bhutan had reported 21 deaths due to COVID-19 as of April 13, 2024.

To estimate county of residence of Filipinx healthcare workers who died of COVID-19, we retrieved data from the Kanlungan website during the month of December 2020.22 In deciding who to include on the website, the AF3IRM team that established the Kanlungan website set two standards in data collection. First, the team found at least one source explicitly stating that the fallen healthcare worker was of Philippine ancestry; this was mostly media articles or obituaries sharing the life stories of the deceased. In a few cases, the confirmation came directly from the deceased healthcare worker's family member who submitted a tribute. Second, the team required a minimum of two sources to identify and announce fallen healthcare workers. We retrieved 86 US tributes from Kanlungan, but only 81 of them had information on county of residence. In total, 45 US counties with at least one reported tribute to a Filipinx healthcare worker who died of COVID-19 were identified for analysis and will hereafter be referred to as “Kanlungan counties.” Mortality data by county, race, and ethnicity came from the National Center for Health Statistics (NCHS).24 Updated weekly, this dataset is based on vital statistics data for use in conducting public health surveillance in near real time to provide provisional mortality estimates based on data received and processed by a specified cutoff date, before data are finalized and publicly released.25 We used the data released on December 30, 2020, which included provisional COVID-19 death counts from February 1, 2020 to December 26, 2020—during the height of the pandemic and prior to COVID-19 vaccines being available—for counties with at least 100 total COVID-19 deaths. During this time period, 501 counties (15.9% of the total 3,142 counties in all 50 states and Washington DC)26 met this criterion. Data on COVID-19 deaths were available for six major racial/ethnic groups: Non-Hispanic White, Non-Hispanic Black, Non-Hispanic Native Hawaiian or Other Pacific Islander, Non-Hispanic American Indian or Alaska Native, Non-Hispanic Asian (hereafter referred to as Asian American), and Hispanic. People with more than one race, and those with unknown race were included in the “Other” category. NCHS suppressed county-level data by race and ethnicity if death counts are less than 10. In total, 133 US counties reported COVID-19 mortality data for Asian Americans. These data were used to calculate the percentage of all COVID-19 decedents in the county who were Asian American. We used data from the 2018 American Community Survey (ACS) five-year estimates, downloaded from the Integrated Public Use Microdata Series (IPUMS) to create county-level population demographic variables.27 IPUMS is publicly available, and the database integrates samples using ACS data from 2000 to the present using a high degree of precision.27 We applied survey weights to calculate the following variables at the county-level: median age among Asian Americans, average income to poverty ratio among Asian Americans, the percentage of the county population that is Filipinx, and the percentage of healthcare workers in the county who are Filipinx. Healthcare workers encompassed all healthcare practitioners, technical occupations, and healthcare service occupations, including nurse practitioners, physicians, surgeons, dentists, physical therapists, home health aides, personal care aides, and other medical technicians and healthcare support workers. County-level data were available for 107 out of the 133 counties (80.5%) that had NCHS data on the distribution of COVID-19 deaths among Asian Americans, and 96 counties (72.2%) with Asian American healthcare workforce data. The ACS 2018 five-year estimates were also the source of county-level percentage of the Asian American population (alone or in combination) who are Filipinx.8 In addition, the ACS provided county-level population counts26 to calculate population density (people per 1,000 people per square mile), estimated by dividing the total population by the county area, then dividing by 1,000 people. The county area was calculated in ArcGIS 10.7.1 using the county boundary shapefile and projected to Albers equal area conic (for counties in the US contiguous states), Hawai’i Albers Equal Area Conic (for Hawai’i counties), and Alaska Albers Equal Area Conic (for Alaska counties).20

Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

The difficulties of death figures

This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

Philippines recorded 1339248 Coronavirus Recovered since the epidemic began, according to the World Health Organization (WHO). In addition, Philippines reported 50351 Coronavirus Deaths. This dataset includes a chart with historical data for Philippines Coronavirus Recovered.

Context

Excel dataset with the following columns: Case No., Age, Sex, Nationality, Status, Transmission. Data were extracted from https://endcov.ph/cases/

Acknowledgements

Medina, Michael Arieh (2020), “Data for: Age as a Risk Factor of COVID-19 Mortality in the Philippines”, Mendeley Data, V2, doi: 10.17632/gxxnmgcfnd.2

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

This Project Tycho dataset includes a CSV file with COVID-19 data reported in PHILIPPINES: 2019-12-30 - 2021-07-31. It contains counts of cases, deaths, and demographics. 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", "Republic of Philippines Department of Health COVID-19 Website Dashboard", "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.

PurposeThis study was performed to determine the clinical biomarkers and cytokines that may be associated with disease progression and in-hospital mortality in a cohort of hospitalized patients with RT-PCR confirmed moderate to severe COVID-19 infection from October 2020 to September 2021, during the first wave of COVID-19 pandemic before the advent of vaccination.Patients and methodsClinical profile was obtained from the medical records. Laboratory parameters (complete blood count [CBC], albumin, LDH, CRP, ferritin, D-dimer, and procalcitonin) and serum concentrations of cytokines (IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-18, IFN-γ, IP-10, TNF-α) were measured on Days 0-3, 4-10, 11-14 and beyond Day 14 from the onset of illness. Regression analysis was done to determine the association of the clinical laboratory biomarkers and cytokines with the primary outcomes of disease progression and mortality. ROC curves were generated to determine the predictive performance of the cytokines.ResultsWe included 400 hospitalized patients with COVID-19 infection, 69% had severe to critical COVID-19 on admission. Disease progression occurred in 139 (35%) patients, while 18% of the total cohort died (73 out of 400). High D-dimer >1 µg/mL (RR 3.5 95%CI 1.83–6.69), elevated LDH >359.5 U/L (RR 1.85 95%CI 1.05–3.25), lymphopenia (RR 1.91 95%CI 1.14–3.19), and hypoalbuminemia (RR 2.67, 95%CI 1.05–6.78) were significantly associated with disease progression. High D-dimer (RR 3.95, 95%CI 1.62–9.61) and high LDH (RR 5.43, 95%CI 2.39–12.37) were also significantly associated with increased risk of in-hospital mortality. Nonsurvivors had significantly higher IP-10 levels at 0 to 3, 4 to 10, and 11 to 14 days from illness onset (p<0.01), IL-6 levels at 0 to 3 days of illness (p=0.03) and IL-18 levels at days 11-14 of illness (p<0.001) compared to survivors. IP-10 had the best predictive performance for disease progression at days 0-3 (AUC 0.81, 95%CI: 0.68–0.95), followed by IL-6 at 11-14 days of illness (AUC 0.67, 95%CI: 0.61–0.73). IP-10 predicted mortality at 11-14 days of illness (AUC 0.77, 95%CI: 0.70–0.84), and IL-6 beyond 14 days of illness (AUC 0.75, 95%CI: 0.68–0.82).ConclusionElevated D-dimer, elevated LDH, lymphopenia and hypoalbuminemia are prognostic markers of disease progression. High IP-10 and IL-6 within the 14 days of illness herald disease progression. Additionally, elevated D-dimer and LDH, high IP-10, IL-6 and IL-18 were also associated with mortality. Timely utilization of these biomarkers can guide clinical monitoring and management decisions for COVID-19 patients in the Philippines.

As of March 8, 2023, there were approximately 276.4 thousand coronavirus (COVID-19) cases in Quezon City in the Philippines. Of these cases, about 2.68 thousand patients died and around 276.6 thousand recovered.

On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit the following sources: World Health Organization (WHO)For more information, visit the Johns Hopkins Coronavirus Resource Center.-- Esri COVID-19 Trend Report for 3-9-2023 --0 Countries have Emergent trend with more than 10 days of cases: (name : # of active cases) 41 Countries have Spreading trend with over 21 days in new cases curve tail: (name : # of active cases)Monaco : 13, Andorra : 25, Marshall Islands : 52, Kyrgyzstan : 79, Cuba : 82, Saint Lucia : 127, Cote d'Ivoire : 148, Albania : 155, Bosnia and Herzegovina : 172, Iceland : 196, Mali : 198, Suriname : 246, Botswana : 247, Barbados : 274, Dominican Republic : 304, Malta : 306, Venezuela : 334, Micronesia : 346, Uzbekistan : 356, Afghanistan : 371, Jamaica : 390, Latvia : 402, Mozambique : 406, Kosovo : 412, Azerbaijan : 427, Tunisia : 528, Armenia : 594, Kuwait : 716, Thailand : 746, Norway : 768, Croatia : 847, Honduras : 1002, Zimbabwe : 1067, Saudi Arabia : 1098, Bulgaria : 1148, Zambia : 1166, Panama : 1300, Uruguay : 1483, Kazakhstan : 1671, Paraguay : 2080, Ecuador : 53320 Countries may have Spreading trend with under 21 days in new cases curve tail: (name : # of active cases)61 Countries have Epidemic trend with over 21 days in new cases curve tail: (name : # of active cases)Liechtenstein : 48, San Marino : 111, Mauritius : 742, Estonia : 761, Trinidad and Tobago : 1296, Montenegro : 1486, Luxembourg : 1540, Qatar : 1541, Philippines : 1915, Ireland : 1946, Brunei : 2010, United Arab Emirates : 2013, Denmark : 2111, Sweden : 2149, Finland : 2154, Hungary : 2169, Lebanon : 2208, Bolivia : 2838, Colombia : 3250, Switzerland : 3321, Peru : 3328, Slovakia : 3556, Malaysia : 3608, Indonesia : 3793, Portugal : 4049, Cyprus : 4279, Argentina : 5050, Iran : 5135, Lithuania : 5323, Guatemala : 5516, Slovenia : 5689, South Africa : 6604, Georgia : 7938, Moldova : 8082, Israel : 8746, Bahrain : 8932, Netherlands : 9710, Romania : 12375, Costa Rica : 12625, Singapore : 13816, Serbia : 14093, Czechia : 14897, Spain : 17399, Ukraine : 19568, Canada : 24913, New Zealand : 25136, Belgium : 30599, Poland : 38894, Chile : 41055, Australia : 50192, Mexico : 65453, United Kingdom : 65697, France : 68318, Italy : 70391, Austria : 90483, Brazil : 134279, Korea - South : 209145, Russia : 214935, Germany : 257248, Japan : 361884, US : 6440500 Countries may have Epidemic trend with under 21 days in new cases curve tail: (name : # of active cases) 54 Countries have Controlled trend: (name : # of active cases)Palau : 3, Saint Kitts and Nevis : 4, Guinea-Bissau : 7, Cabo Verde : 8, Mongolia : 8, Benin : 9, Maldives : 10, Comoros : 10, Gambia : 12, Bhutan : 14, Cambodia : 14, Syria : 14, Seychelles : 15, Senegal : 16, Libya : 16, Laos : 17, Sri Lanka : 19, Congo (Brazzaville) : 19, Tonga : 21, Liberia : 24, Chad : 25, Fiji : 26, Nepal : 27, Togo : 30, Nicaragua : 32, Madagascar : 37, Sudan : 38, Papua New Guinea : 38, Belize : 59, Egypt : 60, Algeria : 64, Burma : 65, Ghana : 72, Haiti : 74, Eswatini : 75, Guyana : 79, Rwanda : 83, Uganda : 88, Kenya : 92, Burundi : 94, Angola : 98, Congo (Kinshasa) : 125, Morocco : 125, Bangladesh : 127, Tanzania : 128, Nigeria : 135, Malawi : 148, Ethiopia : 248, Vietnam : 269, Namibia : 422, Cameroon : 462, Pakistan : 660, India : 4290 41 Countries have End Stage trend: (name : # of active cases)Sao Tome and Principe : 1, Saint Vincent and the Grenadines : 2, Somalia : 2, Timor-Leste : 2, Kiribati : 8, Mauritania : 12, Oman : 14, Equatorial Guinea : 20, Guinea : 28, Burkina Faso : 32, North Macedonia : 351, Nauru : 479, Samoa : 554, China : 2897, Taiwan* : 249634 -- SPIKING OF NEW CASE COUNTS --20 countries are currently experiencing spikes in new confirmed cases:Armenia, Barbados, Belgium, Brunei, Chile, Costa Rica, Georgia, India, Indonesia, Ireland, Israel, Kuwait, Luxembourg, Malaysia, Mauritius, Portugal, Sweden, Ukraine, United Kingdom, Uzbekistan 20 countries experienced a spike in new confirmed cases 3 to 5 days ago: Argentina, Bulgaria, Croatia, Czechia, Denmark, Estonia, France, Korea - South, Lithuania, Mozambique, New Zealand, Panama, Poland, Qatar, Romania, Slovakia, Slovenia, Switzerland, Trinidad and Tobago, United Arab Emirates 47 countries experienced a spike in new confirmed cases 5 to 14 days ago: Australia, Austria, Bahrain, Bolivia, Brazil, Canada, Colombia, Congo (Kinshasa), Cyprus, Dominican Republic, Ecuador, Finland, Germany, Guatemala, Honduras, Hungary, Iran, Italy, Jamaica, Japan, Kazakhstan, Lebanon, Malta, Mexico, Micronesia, Moldova, Montenegro, Netherlands, Nigeria, Pakistan, Paraguay, Peru, Philippines, Russia, Saint Lucia, Saudi Arabia, Serbia, Singapore, South Africa, Spain, Suriname, Thailand, Tunisia, US, Uruguay, Zambia, Zimbabwe 194 countries experienced a spike in new confirmed cases over 14 days ago: Afghanistan, Albania, Algeria, Andorra, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burma, Burundi, Cabo Verde, Cambodia, Cameroon, Canada, Central African Republic, Chad, Chile, China, Colombia, Comoros, Congo (Brazzaville), Congo (Kinshasa), Costa Rica, Cote d'Ivoire, Croatia, Cuba, Cyprus, Czechia, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Eswatini, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kiribati, Korea - South, Kosovo, Kuwait, Kyrgyzstan, Laos, Latvia, Lebanon, Lesotho, Liberia, Libya, Liechtenstein, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Marshall Islands, Mauritania, Mauritius, Mexico, Micronesia, Moldova, Monaco, Mongolia, Montenegro, Morocco, Mozambique, Namibia, Nauru, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, North Macedonia, Norway, Oman, Pakistan, Palau, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Samoa, San Marino, Sao Tome and Principe, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, Somalia, South Africa, South Sudan, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Taiwan*, Tajikistan, Tanzania, Thailand, Timor-Leste, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Tuvalu, US, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Vanuatu, Venezuela, Vietnam, West Bank and Gaza, Yemen, Zambia, Zimbabwe Strongest spike in past two days was in US at 64,861 new cases.Strongest spike in past five days was in US at 64,861 new cases.Strongest spike in outbreak was 424 days ago in US at 1,354,505 new cases. Global Total Confirmed COVID-19 Case Rate of 8620.91 per 100,000Global Active Confirmed COVID-19 Case Rate of 37.24 per 100,000Global COVID-19 Mortality Rate of 87.69 per 100,000 21 countries with over 200 per 100,000 active cases.5 countries with over 500 per 100,000 active cases.3 countries with over 1,000 per 100,000 active cases.1 country with over 2,000 per 100,000 active cases.Nauru is worst at 4,354.54 per 100,000.

Excel dataset with the following columns: Case No., Age, Sex, Nationality, Status, Transmission. Data were extracted from https://endcov.ph/cases/

As of April 21, 2023, there were over 166 thousand coronavirus (COVID-19) cases within Manila City in the Philippines. Of these cases, about roughly 1.9 thousand patients died and around 163.8 thousand recovered.

This comprehensive synthesis of severe COVID-19 risk factors specific to the Asia-Pacific (APAC) region addresses gaps in previous global studies, which often overlook regional demographic, epidemiological, and healthcare system variations. Three databases (PubMed, Ovid MedLine, Scopus) and two preprint platforms (BioRxiv, MedRxiv) were searched between December 1, 2019, and March 31, 2023. English-language publications from 11 APAC countries/regions (Australia, Hong Kong, Japan, Macau, New Zealand, Philippines, Singapore, South Korea, Taiwan, Thailand and Vietnam) reporting conditions associated with severe COVID-19 outcomes in adults (aged ≥16 years) were included. Of 295 publications screened, 123 met inclusion criteria, mostly from South Korea (n = 68) and Japan (n = 23). Common risk factors included older age, male sex, obesity, diabetes, heart failure, renal disease, and dementia. Less commonly hypertension, chronic obstructive pulmonary disease, cardio-and cerebrovascular disease, immunocompromise, autoimmune disorders, and mental illness were reported. To date, no prior region-specific synthesis of risk factors for severe COVID-19 outcomes across the APAC region has been identified. The findings support the development of tailored vaccination strategies and public health interventions at both national and regional levels, helping ensure high-risk populations are prioritized in ongoing COVID-19 prevention and management efforts.

As of April 21, 2023, there were about 182.2 thousand coronavirus (COVID-19) cases within Laguna in the Philippines. Of these cases, about 1.69 thousand patients died and around 180.4 thousand recovered.

As of April 21, 2023, there were around 24.1 thousand confirmed cases of coronavirus (COVID-19) within San Juan City in the Philippines. Of these cases, around 23.7 thousand recovered and 353 died because of the virus.

The outbreak of the novel coronavirus in Wuhan, China, saw infection cases spread throughout the Asia-Pacific region. By April 13, 2024, India had faced over 45 million coronavirus cases. South Korea followed behind India as having had the second highest number of coronavirus cases in the Asia-Pacific region, with about 34.6 million cases. At the same time, Japan had almost 34 million cases. At the beginning of the outbreak, people in South Korea had been optimistic and predicted that the number of cases would start to stabilize. What is SARS CoV 2?Novel coronavirus, officially known as SARS CoV 2, is a disease which causes respiratory problems which can lead to difficulty breathing and pneumonia. The illness is similar to that of SARS which spread throughout China in 2003. After the outbreak of the coronavirus, various businesses and shops closed to prevent further spread of the disease. Impacts from flight cancellations and travel plans were felt across the Asia-Pacific region. Many people expressed feelings of anxiety as to how the virus would progress. Impact throughout Asia-PacificThe Coronavirus and its variants have affected the Asia-Pacific region in various ways. Out of all Asia-Pacific countries, India was highly affected by the pandemic and experienced more than 50 thousand deaths. However, the country also saw the highest number of recoveries within the APAC region, followed by South Korea and Japan.