Initial COVID-19 Philippine Provincial Estimates and Projections

(Medium-risk estimates to set the workable minimum requirements for LGUs)

--UPLB Biomathematics Team--

The UPLB Biomathematics Team conducts free consultations. Contact us if you want to know the details of our projections (; +639777305217).

Mathematical models in epidemiology are auxiliary tools in formulating preventive and mitigation strategies to control the spread of the disease. In this site, results regarding the projected number of infected individuals and fatalities are presented as well as the number of hospital beds and intensive care units needed. Sample simulations of outbreak scenarios are presented per province.

Disclaimer: The models and results in this website are for academic purposes. Caution must be observed in interpreting the quantitative insights, and these should not replace in any way the official announcements by WHO, IATF, NTF, DOH, LGUs and other government institutions. Models can be used as intelligent input during decision-making but users of the model should always check if the assumptions used fit the system or situation. Models and model results should be interpreted with guidance from experts. Numbers presented here have prediction errors. The model results are subject to updates as time progresses and more datasets are received.

The figures displayed here indicate the projected possible spread of COVID-19 in each province. These figures do not reflect real-time or actual data. For real-time tracking, please visit, or

For questions and technical details, please communicate with Assistant Professor Christian Alvin H. Buhat ( or Dr. Jomar F. Rabajante ( Please also inform us if you find errors in the maps, estimates and other information.

Projections are as of 06 April 2020.

This map shows the number of imported or initial cases that can start an outbreak (99% probability; R0=2). Since there is delay in the detection and reporting of new cases, it is suggested to multiply the outbreak threshold by 60%; another 50% can be multiplied to account for the mobility of the people.

Effective surveillance and contact tracing can be done to prevent the establishment of the disease in a location.

Computations by Peter Julian Cayton (UP Diliman) and Jomar Rabajante (UPLB); Reference:

Remark: R0 is the average number of people an infected individual can directly infect in a susceptible population (which is related to the infection or transmission rate).

Visit the maps section of for the probability of outbreak layers.

This map shows the possible number of infected individuals during the whole epidemic period.

This map shows the possible number of expired cases (mortality) during the whole epidemic period. Fatality risk may be halved as more tests are conducted.

This map shows the projected number of hospital beds for severe and critical cases during the peak of the epidemics.

This map shows the projected number of intensive care units for critical cases during the peak of the epidemics.

Population-Density-Based Regional Estimations with Basic Reproductive Number R0=2.5*

Remark: Epidemic peak time may be asynchronous. Fatality risk may be halved as more tests are conducted.

Infection and fatality risks are projected for the whole epidemic period.

Number of beds and ICUs are projected for the duration of the epidemic peak.

*Computations for the other R0 values are available (regional, municipal and barangay-level). Please contact Dr. Jomar F. Rabajante (

This may change as more tests are conducted. Formula: number of deaths in age group i divided by the number of cases in age group i.

Refer to the following dashboard for the details:

Reproductive number is a measure of the "contagiousness" of a disease. It is the average number of susceptible individuals that an infectious individual can directly infect. R>1 could lead to an outbreak; it is advisable to maintain R<1.

Refer to the real-time tracker here:

instantaneous growth rate

constant growth rate

These charts show the doubling time of the cumulative number of reported cases (based on the symptom onset date). A larger value of doubling time is a good sign that the spread of the disease is slowing down.

Refer to the real-time tracker here:

Projected social contact among age groups in the Philippines

This table shows the age groups that are more likely to have higher number of interactions with the other age groups, and with the vulnerable age class (e.g., 65 year-old and above).


Multiple metrics are needed to monitor the situation:

Is 60k detected cases in end of July (DAY 180) possible? Yes. But the future can have different many possibilities. We can control the spread of COVID-19 by strictly following the health standards. While we continue our economic activities, please do not be complacent.

Projections up to December 2020 (variations depend on mobility)

Projections up to July 2020

Projected time-varying reproductive number up to July 2020

Simulations made are through the collective efforts of the UPLB Biomathematics Team.