The growing cases of the COVID-19 pandemic is exacerbated by a widespread of misinformation published in various media platforms today. This is the reason why the L4H portal was created in order to inform the public about the condition of the country thru data-driven analysis and facts. The COVID-19 RISK TRACKER IN THE PHILIPPINES is sponsored by L4H and Cirrolytix Research Services which has the objective to enhance the portal with the purpose of empowering the LGUs to make faster and better decisions supported by data and insight. Insights are further improved by increasing the scope of data processed to include regional and provincial levels, expanding learnings by further exploring the DOH data drop and streamlining the overall visual and interactive experience of its users.

2. TEAM DATA DOPE
Raine Catenza
Roxette Japitana
Keith Monreal
Joe Olivare

3. COVID-19 RISK TRACKER IN THE
PHILIPPINES

4. IINTRODUCTION

5. “… WHO commits to strengthening health
information systems and supports the timely
sharing of data, which together with quick action to
contain transmission is critical in saving lives.”
- Dr. Rabindra Abeyasinghe
- WHO Representative in the Philippines
IINTRODUCTION

6. Started a project that aims to
provide data-driven analysis to
fight against COVID-19 in the
Philippines
INTRODUCTION

7. The Analytics Process
1. Problem Framing
2. Analytics Problem Framing
3. Data Gathering and Processing
4. Data Cleaning
5. COVID-19 Risk Index Model
6. Visualization and Insights
7. Presentation and Recommendation
INTRODUCTION

8. Business Problem
Is it possible to use data
to measure the epidemic
risk index in LGU level to
fight against COVID-19?
INTRODUCTION

9. CURRENT L4H WEBSITE

10. CURRENT L4H WEBSITE

11. ANALYTICS PROBLEM
FRAMING
01
02
03
How can we enhance
the use of COVID Risk
Index Model in helping
LGUs asses their risk?
How to enhance
the user experience
of existing website?
How can the other DOH Data Drop
files aid in providing actionable
insights to the LGUs?

12. Data Prep &
Gathering
DOH Data Drop
Geospatial file of the Ph
Census of Population
DOF Local Budget /circular
Data
Cleaning
COVID-19
Risk Index
Model
Visualization
Python script for Geospatial file &
DOH Data Drop
Excel cleaning for PSGC file
Normalization using Python
Time-Varying Effective
Reproduction Number (Rt) using R
package
Tableau for Dashboard, Case
Exploration Portal, COVID risk
index model
DATA REQUIREMENTS

13. DATA REQUIREMENTS
CHALLENGES
External sources for the
epidemic risk indicator
01
SOLUTION
Communicate with the
experts in the field for
external data to be used
DATA
GATHERING
&
PREPARATION

14. DATA REQUIREMENTS
CHALLENGES
• DOH Data Drop unclean
• Joining of DOH Data Drop
with Geospatial File for
Data Visualization
02
SOLUTION
• Python script for
inconsistent data and for
matching and addition of
PSGC
• Python script for addition
of PSGC for data
visualization and matching
of regions, provinces,
cities
DATA
CLEANING

15. DATA REQUIREMENTS
CHALLENGES
• Not all members are
familiar with using R
language
• Data are not provided
• Different file formats of
external data for
computation
03
SOLUTION
• Self study and consultation
with R experts
• Communicate with the
author and experts
• Manual inputting of
external values
COVIDE 19
RISK INDEX
MODEL

16. DATA REQUIREMENTS
CHALLENGES
Joining of different sources
04
SOLUTION
• Self study and consultation
with tableau experts
• Use of python script for
joining data sets of
external values
VISUALIZATION
AND
INSIGHTS

17. RISK INDEX
01 Framework
Time-varying Effective Reproduction Number
Additional Features
COVID 19 RISK
INDEX MODEL

18. COVID 19 RISK INDEX
MODEL
HAZARD AND
EXPOSURE
VULNERABILITY
100-RESILIENCE
CAPACITYx x
=

19. COVID 19 RISK INDEX
MODEL
HAZARD & EXPOSURE: How does COVID-19
Virus spread?
TIME-VARYING EFFECTIVE
REPRODUCTION NUMBER

20. COVID 19 RISK INDEX
MODEL
RESILIENCY: LGU Health Budget &
Expenditure
LGU Health Expenditures and
Bayanihan Grant Budget

21. COVID 19 RISK INDEX
MODEL
VULNERABILITY: ADDITIONAL FEATURES ON
EPIDEMIC RISK INDICATOR
Mortality Rate Unemployment Rate

22. COVID 19 RISK INDEX
MODEL
COVID RISK INDICATORS

23. DATA VISUALIZATION
02 Dashboard
Epidemic Risk Map
DATA
VISUALIZATION

24. DATA VISUALIZATION
LETICIA
City QUEZON CITY
Occupation LGU OFFICER
OBJECTIVE: to know if their community is at
risk

25. ENHANCED L4H WEBSITE

26. ENHANCED L4H WEBSITE

27. ENHANCED L4H WEBSITE

28. ENHANCED L4H WEBSITE

29. ENHANCED L4H WEBSITE

30. ENHANCED L4H WEBSITE

31. ACTIONABLE INSIGHTS
03 Case Exploraton
ACTIONABLE
INSIGHTS

32. ENHANCED L4H WEBSITE

33. ENHANCED L4H WEBSITE

34. ENHANCED L4H WEBSITE

35. ENHANCED L4H WEBSITE

36. ENHANCED L4H WEBSITE

37. ENHANCED L4H WEBSITE

38. ENHANCED L4H WEBSITE

39. ENHANCED L4H WEBSITE

40. SUMMARY
Objective 1
Implemented COVID 19 Risk model in a
regional and provincial level
Objective 2
Enhanced user experience of
the website
Objective 3
Improved visualization to provide actionable
insights
02
03
01

41. THE TEAM
ROXETTE
JAPITANA
KEITH
MONREAL
JOE
OLIVARE
RAINE
CATENZA

42. QandA

43. RECOMMENDATIONS
FOR FUTURE ENHANCEMENTS
1. Implementation on website
2. Inclusion of other features that are not included due to time
constraint: Proposed List of Features.xlsx
3. Implementation on a higher granularity: Municipality and
Barangay level