Forecast Report No. 11
(June 29, 2020; Updated as of July 2, 2020, 4:00PM)
COVID-19 FORECASTS IN THE PHILIPPINES: NCR, CEBU and COVID-19 HOTSPOTS as of June 25, 2020
Guido David, Ph.D.
Professor, Institute of Mathematics
University of the Philippines and Fellow, OCTA Research (www.octaresearch.com)
Ranjit Singh Rye, MPA
Assistant Professor, Department of Political Science
University of the Philippines and Fellow, OCTA Research (www.octaresearch.com)
Ma Patricia Agbulos, MBM
Associate, OCTA Research (www.octaresearch.com)
Rev. Fr. Nicanor Austriaco, O.P.,Ph.D., S.Th.D., MBA
Professor, Department of Biology,
Providence College and Fellow, OCTA Research
Visiting Professor Designate, College of Science,
Pontifical University of Santo Tomas
With contributions from
Erwin Alampay, Ph.D.
Professor, National College of Public Administrations and Governance
University of the Philippines
Eero Rosini Brillantes
CEO, Blueprint Campaign Consultancy (www.blueprint.ph)
Bernhard Egwolf, Dr. rer. nat.
Associate Professor, Department of Mathematics and Physics,
College of Science, Pontifical University of Santo Tomas
Research Fellow, Research Center for Natural and Applied Sciences,
Pontifical University of Santo Tomas
Emmanuel Lallana, Ph.D.
Alumnus and former faculty member, UP Diliman
CEO, Ideacorp, Inc.
Rodrigo Angelo Ong, MD
Professorial Lecturer, Science Society Program, College of Science
University of the Philippines
Michael Tee, MD, MHPED, MBA
Professor, UP College of Medicine
Chair, Philippine One Health University Network
Benjamin Vallejo Jr. Ph.D.
Professor, Institute of Environmental Science and Meteorology & the
Science Society Program, College of Science, University of the Philippines
1. As of June 25, 2020, the data shows an increase in new Covid-19 cases in the Philippines, from an average of 271 fresh Covid-19 cases per day during Enhanced Community Quarantine (ECQ) in NCR, to 396 fresh cases per day during Modified Enhanced Community Quarantine (MECQ) in NCR, to 583 fresh cases per day during General Community Quarantine (GCQ) in NCR, an increase of 50% from one period to the next. This increase can be explained in part by the increase in testing capacity in the country especially since the positivity rate remains stable. Nonetheless, the positivity rate over the past two weeks is trending up suggesting that the pandemic is spreading more significantly. We believe that this uptick in the positivity rate reflects the current situation in Cebu, which is experiencing a surge in infections.
2. The current reproduction number Rt in the Philippines is still greater than 1, with an estimate of around Rt=1.28, based on the number of new case reports, incidence of fresh cases, and the positive test results of individuals. This indicates that the pandemic is not yet on the downward trend. Moreover, community spread is uneven throughout the archipelago. At this time, the province of Cebu has significantly higher transmission rates than the rest of the country.
3. Based on the current number of cases in the Philippines (including uncategorized cases) and assuming the trends continue, this projects to more than 60,000 Covid-19 cases by July 31, with 1,500 deaths. In NCR, the projection is 27,000 cases by July 31, while in the province of Cebu, the projection is 15,000 cases by July 31, assuming a continued implementation of ECQ. We emphasize that the projected increase in cases and deaths can be prevented by rapidly identifying and breaking chains of viral transmission.
4. Rizal and Leyte have now been classified as High Risk areas.
5. The testing capacity in the Philippines must be increased to at least 20,000 tests per day, while the testing capacity in NCR must be increased to at least 10,000 tests per day, based on recommendations from a study in Harvard University.
6. Hospitalization resource utilization in Cebu City has increased, and occupancy of hospital beds is greater than 70%, while occupancy of ICUs is greater than 60%. On the other hand, occupancy in NCR has gone down, with occupancy of hospital beds at less than 60% while occupancy of ICUs is less than 50%.
7. The number of uncategorized Covid-19 cases, i.e. cases in the database of Department of Health (DOH) that are not ascribed to any region or province, has increased to 2,794, up by 50% from our Report No. 10 published two weeks ago.
8. There is still a backlog of roughly 5,000 cases in the validation of data from the Department of Health.
On June 1, 2020, the National Capital Region (NCR) was placed under General Community Quarantine (GCQ) after being under Modified Enhanced Community Quarantine (MECQ) for two weeks. While community quarantine was still in effect, the relaxation allowed more sectors of the economy to open. In this report, we examine, using data from the Department of Health (DOH) from January 1 to June 25, 2020, the effects of increased mobility on community transmissions. We also would like to emphasize the following:
1. The opinions and recommendations in this report are those of the authors and contributors, and do not reflect the position of the University of the Philippines, University of Santo Tomas, or Providence College.
2. A mathematical model is just an approximation of reality. Models are based on assumptions and are only as good as the data used in its calculations. Despite its limitations, the model has a lot of value and has consistently been accurate in its forecasting capabilities, with an error less than 10%. Using a mathematical model is superior to having no model. The SIR and SEIR models are standards in epidemiological modeling and have been used in peer-reviewed scientific papers and by academic institutions. For example, the UST CoV-2 model by Egwolf and Austriaco, is based on an SEIR model first developed at M.I.T.
3. The period of the study is from March 1 to June 25, 2020.
COVID-19 in the PHILIPPINES
Figure 1 shows the aggregate number of Covid-19 cases in the Philippines from April 8 to June 25, 2020, based on data from the Department of Health (DOH). Three kinds of data are shown. The blue bars illustrate the total number based on unique individuals who tested positive (which will be referred to as test reports), based on the test center reports to DOH. As of June 24, the total number of cases based on test reports is 41,275. The dark blue line shows the total official count of Covid-19 cases based on the date of the report (Date Rep Conf) of DOH. This will be referred in this paper as case reports. As of June 26, this total is 34,073 cases. Finally, the brown line shows the number of Covid-19 cases based on the incidence (date of specimen collection). The brown line thus shows the incidence of “fresh cases.” This will be referred to as incidence reports. In our view, this data better reflects the dynamics of the pandemic compared to the case reports. However, due to the time it takes to obtain and process PCR test results, incidence report data for the past 5-6 days are still mostly incomplete. For this reason, we only included the incidence reports up to June 19, when 32,401 Covid-19 cases were reported.
Note that as of June 19, the number of cases based on test reports is 36,871, which means the actual backlog of the DOH is 4,470 cases. The difference between incidence reports (brown line) and case reports (dark blue line) accounts for the delay in testing. As of June 19, the number of case reports is 28,449. The difference between this number and the number of incidence reports on June 19 is 3,952. This number represents the lag due to testing and to validation of those tests. In other words, the difference between the number of test reports and case reports, which as of June 19 is 8,422 cases, can be broken down into two: a lag due to testing time of 3,952 cases, and the actual DOH lag in processing the data, which is 4,470 cases.
The implications of this in estimating real time data is to use case reports with a loading factor to account for the testing lag, although this will not account for the DOH backlog. Based on historical data of DOH, the loading factor is an additional 10% and 35% of case reports. For reports dating more than one month old, the lag loading is an additional 30%, while for reports that are two weeks to one month old, the loading is an increase of 15 to 25%.We assume the lower value, that is, the lag due to testing is 15%. For example, as of June 26, the number of Covid-19 cases based on the official tally is 34,073. However, the actual number of cases as of June 26, as validated on July 10 when test results have come in, will be around 39,000 cases, or more.
Figure 2 shows the effective reproduction number Rt (shown as a 7-day moving average) using the test reports, the case reports and incidence reports (or fresh cases). Based on the plots, the reproduction number based on case reports is more erratic and prone to spikes that reflect the work efficiency and release of information from the DOH. For example, the surge in Rt to a value of 2.13 by the end of May, which was also observed by a study done at Imperial College of London, is not reflected if we use test reports or incidence reports, because this surge did not reflect the actual dynamics of the pandemic.
In any case, the patterns of transmission are mostly similar using all three data sets, and all give an average value of Rt around 1.28 from June 1 to 19, which corresponds to GCQ in NCR. However, the trends in transmission in the Philippines are starting to increase, with a value of Rt currently at 1.36. This uptick in Rt is being fueled by the current surge of Covid-19 in Central Visayas and Cebu, where the value of Rt is much higher.
Nonetheless, this shows that data for case reports, despite the lags in new test results, can be reasonably used to estimate the rates of transmission. Note that a value of Rt< 1 indicates the pandemic is slowing down and the curve is flattening, while Rt> 1 indicates the pandemic is still spreading.
Figure 3 shows the comparison of average daily new Covid-19 cases, based on incidence, in the Philippines, for the periods from April 16 to May 15, May 16 to 31, and June 1 to 19 (the first period corresponds to ECQ, the second period coincides with MECQ in NCR and Cebu, and the third period coincides with GCQ in NCR and ECQ in Cebu). The plot shows that the average number of Covid-19 cases per day has increased by 50% from one period to the next.
However, as shown in Figure 4, the testing capacity for the Philippines has also increased from April 16, with 3,490 individuals tested, to June 19, with 14,275 individuals tested. This is an increase of 410%. In contrast, the positivity rate, which is the percentage of individual tests that is positive, has remained stable fluctuating between 5% and 9%. The positivity rate is a proxy for community transmission that takes into account a country’s capacity for testing. The somewhat stable positivity rate suggests that the increase in new Covid-19 cases per day between April and June can be explained for the most part by this increase in testing capacity, and not by an increase in community spread of the virus in the entire country.
Nonetheless, given that the positivity rate over the past two weeks is trending up, suggests that the pandemic is spreading more significantly, and should be monitored more closely in the different regions, particularly emerging hotspots of Covid-19. We believe that this uptick in the positivity rate reflects the current situation in Central Visayas and Cebu, which is experiencing a surge in infections.
As shown in Figures 5A and 5B, the testing capacity for the Philippines and for the NCR have increased over the past two months. In the past week, the testing capacity for the country and for NCR has consistently been above 10,000 individuals and 7,000 individuals tested per day respectively. A team at Harvard University has recommended that every municipality with a moderate infection rate, i.e., with less than 1% prevalence of active virus in its population should maintain a testing capacity of 2,500 tests for every death per day. According to the DOH Covid Tracker on June 28, 2020, the Philippines had an average death count of 8 deaths per day, and the NCR had an average death count of 4 deaths per day. We therefore recommend the following minimum numbers of daily tests given in Table 1 below. These numbers will have to increase if the number of deaths begins to rise again, especially in light of the outbreak in Cebu.
As shown in Figures 6A and 6B, the positivity rates for the Philippines and NCR have been relatively stable for the past two months. This suggests that the rate of community transmission has been stable despite the increase in testing capacity. However, the positivity rate has been trending upwards for the past week, suggesting that the rate of spread is increasing both in the country overall and in NCR. Only until we see the positivity rate further reduced, and active cases go down, can we become more comfortable that the government is finally getting the pandemic in NCR under control.
Figure 7 shows the projected number of total Covid-19 cases in the Philippines. The projections were based on an assumed value of Rt = 1.18. This is slightly lower than the average reproduction number in the Philippines since June 1, which is Rt = 1.28. The projections show more than 65,000 Covid-19 cases by July 31. Using a lower value of Rt = 1.09, the projections still lead to more than 60,000 cases by the end of July. Using the average value of Rt = 1.28 leads to more than 70,000 cases by the end of July. On the other hand, the death rate has been slowing down, and we estimate a total of 1,500 Covid-19 deaths in the Philippines by July 31. Again, we emphasize that the projected increase in cases and deaths can be prevented by rapidly identifying and breaking chains of viral transmission.
Figure 8A shows the distribution of active Covid-19 cases (total number of cases less the number of deaths and recoveries) in the Philippines. Only 3.4% of active cases are asymptomatic, while 96% of reported cases are “mild” or symptomatic. The number of asymptomatic cases is likely to be under-reported, especially since testing is not performed on individuals who are not symptomatic. A recent review of the literature reveals that asymptomatic persons seem to account for approximately 40% to 45% of Covid-19 infections (Oran and Topol, 2020).The actual number of active asymptomatic cases may be more than 8,000 cases. To illustrate, if we assume an additional 8,700 asymptomatic Covid-19 cases, the resulting distribution, shown in Figure 8B, would be 30% asymptomatic cases and 70% mild to moderate cases. Under this scenario, the infected fatality ratio (IFR) is 2.9%, which is still within the range of CFR reported for Covid-19 in many parts of the world. The current case fatality rate (CFR) in the Philippines based on this data is 3.7%.
The number of repatriates, or Overseas Filipino workers (OFWs) that have tested positive for Covid-19 as of June 25 is 1,845, with 1,778 listed as active. There has been one death.
The number of uncategorized cases in the DOH data is 2,794, with 2,758 listed as active. This includes 209 recent cases (i.e. the incidence date is between June 19 and 25). The number of uncategorized cases as of June 11 (see our report no. 10) was 1,855. This means that over 2 weeks, the uncategorized cases increased by 50%. The proportion of uncategorized cases remained at around 8% of all Covid-19 cases in the Philippines. Given that 1 out of every 12 Covid-19 cases in the country cannot be identified as to location, the task of tracing and isolation becomes even more difficult.
COVID-19 MONITORING IN NCR
In NCR, the number of Covid-19 cases is 16,727 as of June 25, with 822 deaths (CFR of 4.9%). The higher CFR in NCR suggests a high number of undetected, asymptomatic cases in NCR. The average number of new cases from June 1 to 25 (during GCQ) is 230, which represents an increase of 12% from the number of new cases during MECQ. The average reproduction number Rt in NCR during the period of GCQ is 1.15. However, the recent 7-day average is higher, at around Rt = 1.28. Using the same reproduction number, this projects to almost 30,000 cases with 860 deaths in NCR by July 31, with a lower estimate of 27,000 cases if transmissions decrease. The number of new cases, at 22 per million of population per day, indicates that NCR remains a high risk area for Covid-19.
As seen in Figure 9, the hospitalization resource utilization in NCR is gradually decreasing. Hospital bed occupancy in NCR is less than 60%, while occupancy of ICUs (intensive care units) is less than 50%.
COVID-19 MONITORING IN CEBU
In the province of Cebu, the number of Covid-19 cases as of June 8 was around 3,400. That number nearly doubled to more than 6,400 by June 25. Although the reproduction number Rt in Cebu province has decreased from 2.0 since our previous report, the value of Rt in Cebu from June 16 has been decreasing, indicating that transmissions remain high but the pandemic is slowing down. The implementation of ECQ in Cebu from June 16 has reduced the number of Covid-19 cases. The number of cases in Cebu by June 30 will be less than 8,000, lower than the projection of 11,000 in our Report No. 10, based on Rt = 2.0. Assuming a continued decrease in transmissions due to ECQ, this projects to 15,000 cases in the province of Cebu by July 31. On the other hand, if quarantine measures are relaxed, we could see a surge of 20,000 to 30,000 cases in Cebu province by July 31, based on transmission rates during MECQ in Cebu.
Figure 10 shows the hospitalization resource utilization in Cebu City. The hospitalization resource utilization has been increasing until the re-implementation of ECQ on June 16. Occupancy of beds in Cebu City is more than 70%, while occupancy of ICUs is more than 60%. This increase reveals that there is a genuine surge of community infection in Cebu City at this time that justifies the imposition of the stricture quarantine measures.
The provinces in this list have seen increases in the number of Covid-19 cases. We use the metric in our previous report, wherein a province with at most 1 new Covid-19 case per day per million of population over the past 2 weeks is at low risk, if that number is greater than 1 then it is at medium risk. A region with substantial community transmissions is classified as high risk. The number in parenthesis indicates the number of cases reported from June 12 to 25.
Abra (4) Aklan (1) Albay (10)
Antique (1) Apayao (7) Basilan (1)
Bataan (5) Batangas (21) Bohol (17)
Bukidnon (3) Cagayan (2) Camarines Norte (1)
Camarines Sur (6) Capiz (2) Catanduanes (1)
Cotabato (4) Davao de Oro (5) Davao Del Norte (3)
Davao Oriental (1) Guimaras (1) Ifugao (3)
Ilocos Norte (2) Ilocos Sur (1) Iloilo (31)
Isabela (2) Kalinga (7) La Union (7)
Maguindanao (3) Marinduque (1) Misamis Occidental (7)
Misamis Oriental (11) Mountain Province (1) Negros Occidental (38)
Negros Oriental (8) Nueva Ecija (5) Occidental Mindoro (1)
Oriental Mindoro (1) Palawan (8) Pampanga (10)
Pangasinan (14) Quezon (10) Surigao Del Norte (5)
Surigao Del Sur (6) Tarlac (1) Zambales (2)
Zamboanga Del Sur (8)
Agusan Del Norte (38) Benguet (30) Bulacan (68)
Cavite (87) Davao Del Sur (32) Laguna (65)
Lanao Del Sur (22) Samar (38) Southern Leyte (33)
Cebu (2,568) Leyte (156) NCR (3,635)
SUMMARY AND RECOMMENDATIONS:
1. We are still in a situation where there is significant community transmission in the Philippines. Our estimate of the reproduction number of the virus in the country is around 1.28. Moreover, the community spread is uneven throughout the archipelago. At this time, Central Visayas, especially Cebu City, has significantly higher transmission rates than the rest of the country. Assuming that the reproduction number, Rt remains and there is no significant change in the interventions and strategies by government, based on our projections, by July 31 there could be an escalation to at least 60,000 cases and 1,500 deaths in the Philippines.
Given that the data received from the DOH appears to have lags and uncategorized cases, the current reproduction number Rt in NCR is estimated at 1.28. This classifies NCR as a high-risk area. The projection for NCR is 27,000 cases by July 31.
In Cebu province, the average reproduction number Rt during ECQ is 1.8. This classifies Cebu as a high-risk area, which means SARS-CoV2 is still spreading in the province. The implementation of interventions by the national and local government in Cebu from June 16 has reduced the rate of transmission and the value of the reproduction number Rt. The projection in Cebu province, assuming a continued implementation of ECQ, is 15,000 cases by July 31.Relaxing the quarantine may cause an escalation of 20,000 to 30,000 cases by July 31.
In our view, the aforementioned national and local projections represent a significant increase in transmissions and is a serious cause for concern that needs to be examined and given appropriate and immediate response by the government.
To this end, we recommend that the government review its national strategy to combat Covid-19 in the country. The government must re-examine and re-calibrate its strategies to ensure that the transmission of SARS-CoV2 virus does not further increase beyond the capacity of the health care system to respond. This requires having clear targets to measure whether the strategies are working, such as keeping positivity rates low (below 7%), and active cases trending down.
Furthermore, the easing of quarantine restrictions must be matched with more pandemic surveillance, effective strategies for social distancing, and compliance with other health protocols including vigorous promotion of personal hygiene practices, wearing of masks and other personal protective equipment (PPE) and increased testing, tracing, and isolation as the working population increases their exposure especially in high risk areas such as NCR and Cebu.
Moreover, the further opening up of the economy or the changing of quarantine status are major government decisions that should be made with a clearer picture of the pandemic based on reliable data.
If the aforementioned progressive increase continues, we could possibly experience exponential growth in the number of cases and deaths and an overwhelming of our health care capacity, seriously compromising our collective efforts to contain the virus.
2. There is an urgent need to scale up capacities of our health care system. The government must ensure the following: (1) increased capacity of the national health care system to deal with potential outbreaks, (2) sufficient testing capability, including maximization of increased capacity to cope with the expected increase in cases, (3) sufficient PPE supplies for the front-liners, (4) set up more isolation facilities in NCR and around the country, and (5) effective and aggressive contact tracing.
3. While significant progress in testing was achieved, the number of tests conducted per day still falls below the capacity of 30,000 tests per day. To this end, we urge the DOH to continue to expand the testing capacity until we can test a minimum of 10,000 and 20,000 individuals in NCR and the Philippines, respectively. These should be the average number of tests completed daily over a two-week period.
Moreover, where test kits are limited in number and where the number of Covid-19 positive persons are expected to be low (1%-2%), we recommend that the DOH explore “pool-testing” (Tumanan-Mendoza, et al, 2020). This strategy, recently approved by the USFDA, allows the DOH to make Covid-19 testing more efficient. For example, if the BOQ wants to test 100 returning OFWs, it could use 100 tests to test each one, which is the current strategy, OR it could use 10 tests to test 10 pools of 10 individuals. If 1% of the 100 OFWs were infected, 9out of the 10 pooled tests would come out negative, allowing 90 OFWs to be released from quarantine after the two week period. The remaining 10 in the infected pool are then tested individually to identify the infected person. In total, this would use 21 tests instead of 100 tests to identify one infected person out of the 100 original OFWs.
When the positivity rate drops below 5%, we also recommend that the DOH explore expanding its testing capacity beyond symptomatic persons. We suggest that front-liners and high-contact persons, especially health care workers, and workers who supervise the isolation and quarantine facilities of each LGU be tested regularly. This will detect asymptomatic individuals as well as provide the government with a surveillance strategy to detect the hidden spread of the virus.
4. We reiterate that contact tracing (CT) is an important component in the fight against Covid-19. Aggressive contact tracing should be a centerpiece of our strategy against Covid-19. It will allow the government to identify high-risk individuals and target them for isolation/quarantine. This way we can rapidly identify and break chains of viral transmission and avoid reverting to stricter quarantines that hurt the economy and also strain the psychosocial well being of citizens.
But the challenge with CT is that it is labor-intensive and time-consuming. It is in this light, that we urge the DILG to start mobilizing other sectors of society to help, even on a voluntary basis, undertake aggressive contract tracing.
5. The government should urgently scale up other aspects of the test, trace and treat strategy to deal with the continuing challenges of laboratory capacity in places outside the NCR, delays in laboratory testing, the release of test results, and the validation of positive cases. In this light, we urge the DOH to fast track the accreditation of Covid-19 laboratories and deployment of information and other interventions to improve and increase the return time for test results. In order to facilitate efficient contact tracing, test results should be returned by one day for rapid RT-PCR testing or 2-3 days for more standardized RT-PCR testing.
6. We urge the Department of Health (DOH) to resolve issues regarding the accuracy and timeliness of its data on Covid-19 cases in the country. To date, there still exists a significant backlog of around 5,000 cases and 2,794 uncategorized cases in the DOH Covid-19 database. If not urgently resolved, these significant and continuing challenges regarding DOH Covid-19 data will undermine not just the government’s ability to monitor the spread of the virus but also hamper its ability to implement appropriate and timely responses to manage the pandemic on the ground. Without accurate and accessible DOH data on Covid-19, our national and local government officials as well as other stakeholders will not be able to make decisions crucial to managing the pandemic.
7. Given the resumption of some socio-economic activities, the private sector especially businesses must also step-up their efforts to complement the initiatives of government including ensuring safety in workplaces, providing testing as needed, and operationalizing policies to facilitate contact tracing in the workplace. The cooperation of business establishments will significantly reduce the risk of workplace transmission while jump-starting economic recovery.
8. The LGU system will be the key implementor of the national government strategy and program to fight Covid-19. Health service delivery is already devolved to local governments making them important partners especially during this public health crisis. Moving forward, there is a need to strengthen the capability of local government units through the allocation of more resources and through capacity building. It is against this backdrop, that the national government through the support of Congress must ensure that the greater share in the stimulus package and in the national budget be allocated for LGUs to enable them to implement the national strategy to fight Covid-19 and to realize their goal of creating “safe communities” around the country.
9. While an increase in the number of Covid-19 infection is expected with the increased movement of people, the increasing number of Covid-19 cases suggests that the overall strategy may not be working. After 100 days of quarantine, it is high time that government re-examines its strategy to suppressing Covid-19.
In rethinking the current strategy, the government could look at the following three issues.
a) From ‘Command and Control’ to ‘Empowered Execution,’ government has chosen a command and control approach to the public health emergency. In Command and Control, the government specifies everything that should be done, directs activities from the top, demands obedience to rules and procedures and gives very little leeway to lower units to decide things for themselves. Critics point to three weaknesses of the approach: 1) it does not encourage innovation; 2) it is rigid and not flexible; and, 3) it accommodates political loopholes.
An alternative to Command and Control is “Empowered Execution,” where “individuals and teams closest to the problem, armed with unprecedented levels of insights from across the network, offer the best ability to decide and act decisively”. Here the government does not control each and every move of the organization but adopts an enabling rather than directing stance. Applied to the present situation, the role of lead national agencies (like the IATF, NTF) is to empower communities by providing support for the development of anti-COVID action plans that are based on “credible, legitimate and salient (e.g. scale relevant) science and deliberative-analytic processes.”
b) Citizens are part of the Solution NOT part of the Problem. Not only is the government’s approach too top-down, but it also blames citizens (who are “pasaway”) for the failure to contain the virus. But there is evidence (like Google’s mobility study) that people do follow government directives. Rather than treat citizens as part of the problem, it might be more useful to see them as part of the solution. A public campaign on social distancing and hygienic practices would gain more support if the people see themselves as partners in the fight against the pandemic. Treating citizens as partners may even open a new source for innovative and creative solutions.
c) Evidence-based Policy and Decision Making. Policies and decisions should be grounded in the best available scientific evidence generated from data from the field. While experience is valued, it should not be the sole basis for policy or decisions. This approach has two implications. First, medical professionals and scientists should be taking the lead in health emergencies. Second, the government must prioritize the production of quality data. The seven characteristics of quality data are: Accuracy and Precision; Legitimacy and Validity; Reliability and Consistency; Timeliness and Relevance; Completeness and Comprehensiveness; Availability and Accessibility; and, Granularity and Uniqueness. We have commented on this in the past and others have also pointed out that we cannot have evidenced-based decision making if we do not have quality data.
The difference between the old approach and the proposed new one can be illustrated in how to deploy contact tracing.
Contact tracing is globally recognized as among the key tools to cut disease transmission. Unfortunately, the government has not moved decisively on contact tracing. It has yet to hire more contact tracers due to a lack of budget. Admittedly, contact tracing is difficult and laborious. Furthermore, the longer we delay, the more difficult it would be to implement it successfully. But there are no short cuts. We cannot rely on digital contact tracing (or more properly, digital proximity tracing) because we do not have the critical mass for this application to be useful. We need “boots on the ground” – contact tracers to conduct face-to-face interviews with those who have had contact with infected persons. And that is just the first step. We also need them to trace the contacts of the contacts. Even the contacts of the contacts of the contacts.
Aggressive contact tracing can be done centrally (with one agency, like DOH or DILG) running it. Or it can be done with local governments at the lead. The latter has a greater chance of success. A contact tracing program may ask all of the right health/medical questions, but if it isn’t designed in a culturally sensitive manner, it won’t be successful. People will only give truthful responses to those they trust. Thus, employing thousands of contact tracers and deploying them to communities where they are complete strangers is not the formula for success.
Contact tracing teams should also be ICT-enabled. This means that each team has to be equipped with digital devices (laptop, tablet or phablet) to record and to report their findings to LGUs and national agencies. Among the causes of the Covid-19 data problems is that information is collected manually and then encoded. We should avoid this problem when we do aggressive contact tracing. Contact tracing data should be digital at birth. Data could be stored at the local databases but shared with relevant national agencies.
Thus contact tracing teams should be composed of community leaders (Barangay Captain or Kagawad), health workers (from the LGU and/or barangay) and student volunteers from medical and/or health-related courses. These volunteers are expected to be ICT literate as they would be in charge of digital data capture and reporting.
In this empowered execution scenario, the role of the lead national agencies like the IATF is to develop an overall digital contract tracing plan, develop and deploy a decentralized digital contact tracing system and augment the resources of local governments for contact tracing. Local governments with community participation undertake contact tracing that generates quality digital data. This arrangement would be more effective in containing the virus and probably less costly than a command and control model was hiring, training, deploying and managing contact tracing teams is undertaken by a lead national agency.
10. It is time to change gears before we lose control of the situation. We need a new strategy that is characterized by empowered execution, treatment of citizens as partners, and relying on evidence-based policy and decision making. The specific elements of a new approach can be further refined. What is urgent is to recognize that doing more of the same will not lead to better results. We also do not want to remain the laggard in the region in the fight against Covid-19. The nation deserves better.
In closing, without continued vigilance on the part of the government, private sector, civil society, and citizens, this significant community transmission in the country may lead to the pandemic getting out of control. If both national and local governments continue to fail to provide a prompt and adequate response, all our societal and financial sacrifices will be wasted, and we will likely experience another wave. This may lead to yet another round of more stringent restrictions, which could be harder for the government to implement and will likely undermine our economic recovery.
Download a copy of the report here.
1. Department of Health Covid-19 Tracker. Retrieved from:https://www.doh.gov.ph/covid19tracker
2. Egwolf B, Austriaco N, 2020. Mobility-Guided Modeling of the COVID-19 Pandemic in Metro Manila. https://doi.org/10.1101/2020.05.26.20111617
3. Oran D, Topol E, 2020. Prevalence of Asymptomatic SARS-CoV-2 Infection. Annals of Internal Medicine. https://doi.org/10.7326/M20-3012
4. Tumanan-Mendoza B, Genuino R, Bermudez-delos Santos AA, 2020. Should pooled sample testing using RT-PCR be used in screening patients suspected to have COVID-19? Retrieved from: https://www.psmid.org/should-pooled-sample-testing-using-rt-pcr-be-used-in-screening-patients-suspected-to-have-covid-19/
5. David G, Rye, RS, Agbulos, MP, Alampay E, Brillantes ER, Lallana E, Ong RA, Tee M, Vallejo B, 2020. COVID-19 FORECASTS IN THE PHILIPPINES: NCR and CEBU as of June 8, 2020. Retrieved from: https://www.up.edu.ph/covid-19-forecasts-in-the-philippines-ncr-and-cebu-as-of-june-8-2020/
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The findings and recommendations in the report are those of the authors and do not necessarily reflect the official position of the University of the Philippines, University of Santo Tomas, Providence College, or any of its units.