Countries across the globe were affected by the 2019 Coronavirus Disease (COVID-19), an infectious disease caused by the most recently discovered coronavirus SARS-CoV-2. In the Philippines, data from the Department of Health (DOH) showed that it was not until March 6, 2020 that the number of reported cases rose to 5. On March 7, DOH announced that the 5th case of COVID-19 is the first case of local transmission in the country. On March 8, 2020, President Rodrigo Duterte signed Proclamation No. 922 declaring the Philippines under a “State of Public Health Emergency” following the recommendation of the Department of Health to place the Philippines in Code Red Sublevel-1 due to COVID-19. President Duterte announced last March 12 that the entire Metro Manila will be placed into community quarantine effective midnight of March 15 due to the increasing number of community transmission of COVID-19 whose links cannot be established.

The University of the Philippines Resilience Institute, together with the Philippine Red Cross and the Department of Health, in response to the current (COVID-19) pandemic affecting the nation and the globe, would like to learn from this current crisis, document it and create policies and tools that would ensure the survival of the Filipino people for future crises. We have encountered several gaps in our national response in halting the spread of this disease in the country, and have discovered that applying what we were taught or what was written in the existing policies is complex and multifaceted.



Efficiency: Analyzing and Summarizing Complex Data

Complex data and analysis, especially when needs constant updating, could be too technical for the general public. Also, analysis could be time consuming; In a fast pace and highly technical environment, this can be problematic. Reports are usually needed hastily even when dealing with large and complex data. Giving accurate, timely and presentable projections that effectively communicates the urgency of an epidemic crisis is crucial for decision makers

Data Storage, Retrieval and Manipulation

Physical files are prone to loss and difficult retrieval. Having projections and actual progression of diseases being stored in a database is helpful for studies, program and response evaluations. Parameters and data can be adjusted for projection purposes that can be highly valuable for program and disaster response planning.

Data Sharing and Transmission

Having an online platform helps people share and update data in a timely manner in various locations with varying degrees of authorized access, that can be crucial for a speedy response; This ultimately helps efficient resource utilization.


Literature Review

According to Q&A on coronaviruses (COVID-19) (2020), COVID-19 “is the infectious disease caused by the most recently discovered coronavirus. This new virus and disease were unknown before the outbreak began in Wuhan, China, in December 2019.” Studies have found that 1 out of 6 who gets this disease may need special treatment but there are some, about 80%, who recover from it without the need of being treated at all.

Common Symptoms of COVID-19 include: fever, tiredness, dry cough, joint aches and pains, nasal congestion, runny nose, sore throat, and diarrhea (Q&A on coronaviruses (COVID-19), 2020). Those who are at risk from this disease include older people who already have medical problems such as: diabetes, heat problems, and high blood (Q&A on coronaviruses (COVID-19), 2020).

Treatment such as Vaccines and Medicine for COVID-19 are still being studied and formulated (Q&A on coronaviruses (COVID-19), 2020). Today, those who are suffering from this illness are hospitalized to be given the needed care (Q&A on coronaviruses (COVID-19), 2020). Even though there is no cure to the said disease, there are still ways in which the spread of this can be prevented. This includes, frequent washing of hands for about 20 seconds, covering your cough with your bended elbow or a tissue, and maintaining social distancing within 3 feet (Q&A on coronaviruses (COVID-19), 2020). With the shortage of masks, the World Health Organization suggests the rational use of masks which means there is no need to use one if you are not sick or looking after someone who is sick (Q&A on coronaviruses (COVID-19), 2020).



Generally, this study aims to develop a model that could describe COVID-19 transmission dynamics and provide recommendations based on the simulations. It will also be utilized to aid the government in their measures for controlling the epidemic. The methods and results of this study can be used also in other epidemics in the future.

1. To determine key epidemiological metrics describing the spread of the disease based on available data.

2. To identify effective control strategies mitigating the spread of the disease based on optimal control theory, and estimate the values of epidemiological parameters affecting the temporal dynamics of COVID-19

3. To perform hotspot analysis at a barangay level among regions with a growing number of suspect, probable or confirmed cases.

4. To identify potential disease drivers (e.g. patient’s lifestyle, weather, etc.) influencing the spread of COVID-19.

5. To develop a web-based epidemic decision tool for predicting COVID-19 transmission dynamics.


Expected Output(s)

The expected output from this study shall contain the following:

1. Research articles and webinars on disease modeling, in particular COVID-19, and data analytics.

2. An epidemic web-based decision tool and repository of COVID-19 studies.

3. Policy briefs providing recommendations


End-users/Target Beneficiaries

The Department of Health, and possibly the national and local government, will benefit from this research since this will provide data that may foresee possible scenarios and address any issues beforehand. Data can also be utilized as inputs in allocating resources for the improvement of specific scale (municipal, provincial, regional and national) and strengthening measures that were already in place. In due course, the ultimate beneficiaries are the Filipinos because in cases of disaster/epidemic, this will ensure supplementary safety to them.



Conceptual Framework

The Conceptual Framework used in this study is the Spiral Model which anticipates that the system will always need updating and is subject to regular review. The system in this study will be the decision tool created to simulate epidemics predicting their transmission; possible strategies for control of spread; and hotspot analysis at various levels; and potential disease drivers that aid the spread of the virus.

Research Design
The research design will be descriptive and predictive, cross sectional design. In cross sectional study, variables are identified one point in time and the relationships between them are determined.

Site of the study
Human participants will not be utilized in this study, however, anonymized data of those who tested positive in the Philippines will be gathered. The data may come from the different scales (municipal, provincial, regional and national) considering various epidemiological factors or parameters. Sources of data will come from the Department of Health and LGUs.


Plans for Data Processing and Analysis

Review and consolidation of epidemiological factors and parameters will be assessed first. Following that, a collaborative design with mathematical modelers, programmers and data scientists will be conducted as well as consultations with epidemiological experts. Prototyping of the decision tool shall take place. With testing and feedback, the gaps in the decision tool as well as the extent of readiness before launching will be recognized. Trainings for technology transfer, maintenance of the application, as well as updates, will be given periodically as needed.

Ethical/Biosafety Clearance

Human subjects will not be utilized in this project. Instead, epidemiologic data and principles will be applied and integrated. Necessary clearances or exemptions will still be complied by the project.

Research Utilization

Webinars on disease modeling and data analytics can help in capacity building of LGUs and research institutes. Research articles published in journals can improve knowledge of COVID-19 dynamics and control, especially in the Philippine-setting. An epidemic web-based decision tool and repository of COVID-19 studies will provide aid to policy- makers in formulating strategies and guidelines. Policy briefs provide recommendations on possible interventions under various scenarios.


Q&A on coronaviruses (COVID-19). (2020, March 9). Retrieved March 20, 2020, from