Preliminary figures between January to September 2024 indicated that ischaemic heart disease was the leading cause of death in the Philippines. The number of people who died from this illness was estimated at 75,500. Following this, cancer resulted in the deaths of about 43,000 people. Eating habits Heart diseases have been linked to high meat consumption, among others. In the Philippines, pork has been the most consumed meat type, followed closely by chicken. While pork meat is typically produced domestically, the country also imports pork to supplement its supply. However, plant-based food has started gaining popularity among Filipinos. In fact, a 2024 survey revealed that 69 percent of surveyed Filipinos consumed plant-based products, including meat alternatives. Common diseases in the Philippines Aside from heart and cerebrovascular diseases, the Filipino population is also exposed to infections, diabetes, skin diseases, and illnesses resulting from high meat consumption. In 2020, over 700,000 Filipinos contracted acute respiratory tract infections, followed by over 400,000 diagnosed with hypertension. In areas with high exposure to rain, dengue infections and leptospirosis have also become prevalent.

Philippines PH: Cause of Death: by Non-Communicable Diseases: % of Total data was reported at 67.300 % in 2016. This records an increase from the previous number of 67.200 % for 2015. Philippines PH: Cause of Death: by Non-Communicable Diseases: % of Total data is updated yearly, averaging 66.450 % from Dec 2000 (Median) to 2016, with 4 observations. The data reached an all-time high of 67.300 % in 2016 and a record low of 56.500 % in 2000. Philippines PH: Cause of Death: by Non-Communicable Diseases: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Philippines – Table PH.World Bank.WDI: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Non-communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.; ; Derived based on the data from WHO's Global Health Estimates.; Weighted average;

Philippines PH: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data was reported at 32.800 NA in 2016. This records a decrease from the previous number of 32.900 NA for 2015. Philippines PH: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data is updated yearly, averaging 32.900 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 34.400 NA in 2005 and a record low of 31.600 NA in 2000. Philippines PH: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Philippines – Table PH.World Bank.WDI: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

In 2022, the Philippines recorded around ******* dengue cases, indicating a significant increase from the previous year. The number of dengue cases in the country peaked in 2019. Dengue is a disease caused by mosquitos.

Philippines PH: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data was reported at 26.800 % in 2016. This records a decrease from the previous number of 26.900 % for 2015. Philippines PH: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data is updated yearly, averaging 26.900 % from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 28.400 % in 2005 and a record low of 26.800 % in 2016. Philippines PH: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Philippines – Table PH.World Bank.WDI: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

In 2021, there were approximately ******* cases of occupational diseases recorded in the Philippines. The number of diseases related to work in the country peaked in 2013.

According to preliminary data between January and October 2024, *** percent of deaths in the Philippines were caused by chronic lower respiratory diseases. Deaths from such illnesses fluctuated since 2017, with the highest share of deaths reported in 2017 and 2019.

Philippines PH: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data was reported at 21.000 NA in 2016. This records a decrease from the previous number of 21.100 NA for 2015. Philippines PH: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data is updated yearly, averaging 21.800 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 22.700 NA in 2005 and a record low of 21.000 NA in 2016. Philippines PH: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Philippines – Table PH.World Bank.WDI: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

According to preliminary data between January and October 2024, *** percent of deaths in the Philippines were caused by diabetes mellitus diseases. Deaths from such illnesses peaked in 2020. Diabetes mellitus is diagnosed when glucose is high in the blood.

Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretabilty. We also formatted the data into a standard data format.

Each Project Tycho dataset contains case counts for a specific condition (e.g. measles) and for a specific country (e.g. The United States). Case counts are reported per time interval. In addition to case counts, datsets include information about these counts (attributes), such as the location, age group, subpopulation, diagnostic certainty, place of aquisition, and the source from which we extracted case counts. One dataset can include many series of case count time intervals, such as "US measles cases as reported by CDC", or "US measles cases reported by WHO", or "US measles cases that originated abroad", etc.

Depending on the intended use of a dataset, we recommend a few data processing steps before analysis:

• Analyze missing data: Project Tycho datasets do not inlcude time intervals for which no case count was reported (for many datasets, time series of case counts are incomplete, due to incompleteness of source documents) and users will need to add time intervals for which no count value is available. Project Tycho datasets do include time intervals for which a case count value of zero was reported.
• Separate cumulative from non-cumulative time interval series. Case count time series in Project Tycho datasets can be "cumulative" or "fixed-intervals". Cumulative case count time series consist of overlapping case count intervals starting on the same date, but ending on different dates. For example, each interval in a cumulative count time series can start on January 1st, but end on January 7th, 14th, 21st, etc. It is common practice among public health agencies to report cases for cumulative time intervals. Case count series with fixed time intervals consist of mutually exxclusive time intervals that all start and end on different dates and all have identical length (day, week, month, year). Given the different nature of these two types of case count data, we indicated this with an attribute for each count value, named "PartOfCumulativeCountSeries".

WHO: COVID-2019: Number of Patients: Death: New: Philippines data was reported at 0.000 Person in 24 Dec 2023. This stayed constant from the previous number of 0.000 Person for 23 Dec 2023. WHO: COVID-2019: Number of Patients: Death: New: Philippines data is updated daily, averaging 15.000 Person from Jan 2020 (Median) to 24 Dec 2023, with 1425 observations. The data reached an all-time high of 484.000 Person in 28 Sep 2021 and a record low of -5.000 Person in 07 Jun 2023. WHO: COVID-2019: Number of Patients: Death: New: Philippines data remains active status in CEIC and is reported by World Health Organization. The data is categorized under High Frequency Database’s Disease Outbreaks – Table WHO.D002: World Health Organization: Coronavirus Disease 2019 (COVID-2019): by Country and Region (Discontinued). Prior to 03 Feb 2020, data were generated.

Philippines PH: Mortality Rate: Under-5: per 1000 Live Births data was reported at 28.100 Ratio in 2017. This records a decrease from the previous number of 28.600 Ratio for 2016. Philippines PH: Mortality Rate: Under-5: per 1000 Live Births data is updated yearly, averaging 62.750 Ratio from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 102.900 Ratio in 1960 and a record low of 28.100 Ratio in 2017. Philippines PH: Mortality Rate: Under-5: per 1000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Philippines – Table PH.World Bank.WDI: Health Statistics. Under-five mortality rate is the probability per 1,000 that a newborn baby will die before reaching age five, if subject to age-specific mortality rates of the specified year.; ; Estimates Developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development across countries. Under-five mortality rates are higher for boys than for girls in countries in which parental gender preferences are insignificant. Under-five mortality captures the effect of gender discrimination better than infant mortality does, as malnutrition and medical interventions have more significant impacts to this age group. Where female under-five mortality is higher, girls are likely to have less access to resources than boys.

Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretabilty. We also formatted the data into a standard data format.

Each Project Tycho dataset contains case counts for a specific condition (e.g. measles) and for a specific country (e.g. The United States). Case counts are reported per time interval. In addition to case counts, datsets include information about these counts (attributes), such as the location, age group, subpopulation, diagnostic certainty, place of aquisition, and the source from which we extracted case counts. One dataset can include many series of case count time intervals, such as "US measles cases as reported by CDC", or "US measles cases reported by WHO", or "US measles cases that originated abroad", etc.

Depending on the intended use of a dataset, we recommend a few data processing steps before analysis:

• Analyze missing data: Project Tycho datasets do not inlcude time intervals for which no case count was reported (for many datasets, time series of case counts are incomplete, due to incompleteness of source documents) and users will need to add time intervals for which no count value is available. Project Tycho datasets do include time intervals for which a case count value of zero was reported.
• Separate cumulative from non-cumulative time interval series. Case count time series in Project Tycho datasets can be "cumulative" or "fixed-intervals". Cumulative case count time series consist of overlapping case count intervals starting on the same date, but ending on different dates. For example, each interval in a cumulative count time series can start on January 1st, but end on January 7th, 14th, 21st, etc. It is common practice among public health agencies to report cases for cumulative time intervals. Case count series with fixed time intervals consist of mutually exxclusive time intervals that all start and end on different dates and all have identical length (day, week, month, year). Given the different nature of these two types of case count data, we indicated this with an attribute for each count value, named "PartOfCumulativeCountSeries".

WHO: COVID-2019: Number of Patients: Death: To-Date: Philippines data was reported at 66,779.000 Person in 24 Dec 2023. This stayed constant from the previous number of 66,779.000 Person for 23 Dec 2023. WHO: COVID-2019: Number of Patients: Death: To-Date: Philippines data is updated daily, averaging 52,511.000 Person from Jan 2020 (Median) to 24 Dec 2023, with 1425 observations. The data reached an all-time high of 66,779.000 Person in 24 Dec 2023 and a record low of 0.000 Person in 01 Feb 2020. WHO: COVID-2019: Number of Patients: Death: To-Date: Philippines data remains active status in CEIC and is reported by World Health Organization. The data is categorized under High Frequency Database’s Disease Outbreaks – Table WHO.D002: World Health Organization: Coronavirus Disease 2019 (COVID-2019): by Country and Region (Discontinued).

In 2021, the leading illness in the Philippines was acute respiratory infection, with approximately 598,591 people diagnosed with this disease. This was followed by hypertension and animal bites. The morbidity rate of acute respiratory infection per hundred thousand population in the Philippines was at nearly 543.2 in that year.

In 2021, Pangasinan recorded the highest number of deaths by heart diseases in the Ilocos region of the Philippines, accounting for around ***** out of total ****** deaths across the region. On the other hand, the city of Vigan had only *** reported deaths in that year.

Philippines PH: Mortality Rate: Infant: per 1000 Live Births data was reported at 22.200 Ratio in 2017. This records a decrease from the previous number of 22.700 Ratio for 2016. Philippines PH: Mortality Rate: Infant: per 1000 Live Births data is updated yearly, averaging 43.450 Ratio from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 66.100 Ratio in 1960 and a record low of 22.200 Ratio in 2017. Philippines PH: Mortality Rate: Infant: per 1000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Philippines – Table PH.World Bank.WDI: Health Statistics. Infant mortality rate is the number of infants dying before reaching one year of age, per 1,000 live births in a given year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development across countries. Under-five mortality rates are higher for boys than for girls in countries in which parental gender preferences are insignificant. Under-five mortality captures the effect of gender discrimination better than infant mortality does, as malnutrition and medical interventions have more significant impacts to this age group. Where female under-five mortality is higher, girls are likely to have less access to resources than boys.

No of Deaths: Philippines data was reported at 2.000 Person in 07 Aug 2003. This stayed constant from the previous number of 2.000 Person for 11 Jul 2003. No of Deaths: Philippines data is updated daily, averaging 2.000 Person from Apr 2003 (Median) to 07 Aug 2003, with 73 observations. The data reached an all-time high of 2.000 Person in 07 Aug 2003 and a record low of 0.000 Person in 19 Apr 2003. No of Deaths: Philippines data remains active status in CEIC and is reported by World Health Organization. The data is categorized under High Frequency Database’s Disease Outbreaks – Table WHO.D002: World Health Organization: No of Deaths.

2020 saw a surge in malaria-related deaths in the Philippines - the highest in the past 12 years. From just ** deaths in 2009, this figure rose to *** in the current reporting period. The highest number of deaths nationwide was recorded in the region of MIMAROPA.

Malaria is an infectious disease typically transmitted by the bite of an infected mosquito and is common in tropical countries such as the Philippines.

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.