Why I Stopped Mathematical-Modeling of DOH Data. Below is the Story.

“You cannot manage what you cannot measure.”—Peter Ducker

Special COVID-19 Report May 9, 2020

Why I stop Math-Modelling the DOH Data. Below is the history:

From April 15 to May 9, 2020 the Charts would show that no significant change has happen except the increase in recoveries. The Charts below would give us a historical visual understanding of the COVID-19 situation including explanations to the model.

In trying to “flatten the curve”. two-ways can be done to lift the ECQ. One, is the number of infections per day is made equal to the recoveries per day. However, as shown Chart 14.0 it will take months to take effect the ECQ. However, this will only mean that the curve is flattened to prevent the overwhelming of public health system or the number of hospital beds for CODIV-19 patients are greatly reduced. But the number of COVID-19 is still increasing.

In Chart 14.0 the curve will no longer follow the linear regression line but instead the polynomial regression line is followed because the R2 = 0.9939 of the polynomial regression line is much higher the the R2 = 0.9757 of the linear regression line

The other option is to exert all effort to reduce the CODIV-19 infection to zero persons per day and the recovery by 150 persons per day. The Chart 15.0 would show that that the flattening of the curve and a down trend will happen and hopefully would lift the ECQ by the middle of June.

The Chart 15.0 would show the using the polynomial regression line is accurate with R2 = 0.9787 than the linear regression R2 = 0.467.

To achieve Chart 15.0 my recommendation is:

  1. Identifying the communities that is highly vulnerable to COVID-19 such as informal settlers in Metro Manila, the City Jails, Bilibid Prison and the ECQ offenders. The communities may consist of 1000 families or a population of 4000 persons. The houses of the informal settlers do not even comply with the 2-meter spacing. Just imagine if these communities are infected. Immediately the curves will spike uncontrollably. Consequently, the health system is jeopardized. Then we revert to Case 1 or “back-to-zero”. It is going to be a cycle that will damage our economy.

The informal settlers is unique to the Philippines and some Asian countries. We cannot adopt strategies such as Korea, Singapore or other Western countries. It is easier for these countries to recover a pandemic because of the strict implementation of the issuance of building permits. The Philippine government allowed informal settlers to build homes without complying the basic requirements of building permits such as architectural and structural plans. One specific rule in spacing homes is that the wall sides of a house should be 2 meters away from the perimeter of the lot. About 3 meters distance from the front wall to the sidewalk. This is the same building standard being adopted by western countries.

The only way to accomplish this building standard is for the informal settlers be relocated immediately to such areas as Subic on the condition that their present homes in the cities will be upgraded to a decent home for a family. Please note that Subic is almost as big as Singapore and the US Navy has left many housing or covered facilities that can temporarily house the informal settlers.

  • Moving 75 % the informal settlers in Metro Manila to Subic or to provinces where they are welcomed. Like a “Balik-Probinsya” Program. To be more aggressive, the informal settlers will be beneficial of an “On-site Housing Program” and a cooperative program of gaining income.
  • Similarly, the prison settlers be transferred to other jails outside Metro Manila. The news today registered CODIV-19 infected prison settlers.
  • The commercial activity in wet markets or palengke should be reduced to 50%. Social spacing should be mandatory.
  • The OFW and balik-bayans should be strictly quarantined for more than 15 days.
  • For the transportation system, it highly recommended to increase the bus stops to at least 1000 bus stops in Metro Manila and allocating bus routes for this bus stop. This is to ensure social distance for the passengers. When the bus complied with social distancing the bus can by-pass the bus stop. This will also prevent long queue of people waiting for the bus.

Update No.5 COVID-19 Report

[This May 5, 2020 Report is a continuation of the COVID-19 Report issued last April 27, 2020.]   “You cannot manage what you cannot measure.”—Peter Ducker

  • Purpose:

To determine the day when the curve starts to “flatten” based on the available statistical data; and forecast when the ECQ is lifted.

  • Current Situation -April 27, 2020

Based on Report No. 1, Table 3.0 summarizes the statistical data of the comparison of the linear equations from April 15, 2020 to April 26, 2020. It was started last April 15, 2020 when the mass testing started.

We observed that the slope of the equation dropped from m=185.29 to m=173.52 while the intercept rose from c=-604.49 to c=-461.08 during the period of study. The drop in m-slope is significant because despite of the increase in the number of tested persons the “curve” did not increase significantly. However, we observed that in April 26, 2020 the number of infected persons increased to 285 persons when previous recorded COVID-19 infected person was 102 infected persons in April 25, 2020 and 211 in April 24, 2020. This fluctuation has been going on since April 20, 2020. Despite of this changes the slope tends to drop while the intercept rises indicating a downtrend in the curve. However, from April 26, 2020 to May 1, 2020 the slope and the intercept hardly change indicating very slow to no improvement in mitigating the COVID-19 virus.

Table 3.0 Comparison Between Linear Regression Equation vs. Time

DateNumber TestedEquationSlopeInterceptΔ SlopeΔ Intercept
April 1533,450Y=185.29X – 604.48185.29-604.49  
April 1952,817Y=182.19X – 570.81182.19-570.813.1033.68
April 2268,512Y=178.23X – 523.05178.23-523.053.9647.76
April 2684,789Y=173.52X – 461.08173.52-461.084.4161.97
May 01108,680 Y=169.34X- 400.49169.34-400.494.1860.59
May 05126,164 Y=167.53X- 371.19167.53-371.191.8129.30

In Chart 3.0 is a graph representing a statistical data on the day ‘mass’ testing started. It would show that in the blue arrow on the right the linear equation in red dots is below the forecasted ‘orang’ line. On the other hand, the ‘green’ arrow on the left shows the linear regression line is below the ‘blue line’ by c= -604.48. Notice the green line slops downward.

                                                 Chart 3.0 Forecast COVID-19 April 15, 2020 (b)

In Chart 6, the ‘blue arrow’ on the left shows the linear regression in ‘red dots’ is now above the forecasted line indication a stiffer slope after the number of test was increased to 52,817 persons. The ‘green line’ was forecasted as ‘plateauing’ in the graph from a downward trend.

In Chart 9.0, the ‘blue arrow’ on the left shows the linear regression in ‘red dots’ rises further above the forecasted line indicating a stiffer slope after the number of test was increased to 68,532 persons. The ‘green line’ was forecasted as ‘plateauing’ in the graph on a downward.

The Charts shown above will show the effect of the number of recoveries on the number of testing as it increases. Although the rise in slope of the linear regression line, the slope in the equation continue to drop indicating that the health care system is working. However, this do not mean we are “off the hook”. At worst, the linear regression could follow the line shown in ‘dash line’.

In Chart 11.0 shown above shows the “green line” projection has uptrend instead of following the down trending “green line” in Chart 10.0. This indicates that the ECQ is not being implemented as intended.

May 5, 2020

In Chart 12.0 of May 5, 2020, would indicate there is a serious problem in implementing ECQ. Cebu City infection is on the rise. In the news this past few days is about the infections on prison settlers and wet markets. The influx of OFW returnees could have spike the infections. The health personnel is also becoming part of the statistics. Informal settler’s Barangays are being lock-down.

The above situation is best explained by looking at Chart 12.0 and Table 3.0. The forecasted linear regression line (Red Dotted Line) In Chart 12.0 shows a line going up indicating an increase in slope, however, in Table 3.0 would show that the slope increase is minimal and the intercept drop (More Positive) is high. This would indicate the influence of the increase in the number of recoveries during this period where it recorded the highest recoveries that influence the movement of the curve that seems to trend upwards.

We can say therefore that recoveries greatly influence the curve. We can also note that the forecasted curve (solid red line) influence the “green line” and the “orange dash line” to go towards “solid red line” indicating the infections is still on the rise.

May 9, 2020

Looking at Chart 13.0 would indicate almost no improvement in the ECQ implementation. It also shows that the “flattening” of the has not started. It will take drastic steps to move the curve down. The closeness between linear regression line with the green, orange and dash lines only indicate correctness of the forecast or r2 = 0.9904.

From May 1 to May 9, 2020 in Chart 13.0 would show that no significant change has happen except the increase in recoveries. The Charts would give us a visual understanding of the situation historically, in trying to “flatten the curve”. Referring to the Charts, there are two-ways to lift the ECQ. One, is when the number of infections is made equal to the recoveries. However, as shown Chart 14.0 it will take another 2 months to take effect the ECQ.

Table 3.0 Comparison Between Linear Regression Equation vs. Time

DateNumber TestedEquationSlopeInterceptΔ SlopeΔ Intercept
April 1533,450Y=185.29X – 604.48185.29-604.49  
April 1952,817Y=182.19X – 570.81182.19-570.813.1033.68
April 2268,512Y=178.23X – 523.05178.23-523.053.9647.76
April 2684,789Y=173.52X – 461.08173.52-461.084.4161.97
May 01108,680 Y=169.34X – 400.49169.34-400.494.1860.59
May 05126,164 Y=167.53X – 371.19167.53-371.191.8129.30
May 09145,586 Y=165.42X – 333.92165.42-333.922.1137.27

In Chart 16.0 is similar to Chart 14.0 showing that the polynomial regression would follow the green curve when the number of COVID-19 infection is zero per day.

In Chart 17.0 shows the forecast in linear regression is not correlative as in the polynomial line in green dash line where R2 = 0.9779 as against the linear regression of R2 = o.874. This means the forecast in linear regression is no longer applicable.

To ‘flatten and drop’ the curve, we should be ‘very tough and courageous’ in implementing the following suggestions:

  • It can be started by identifying the communities that is highly vulnerable to COVID-19 such as informal settlers in Metro Manila, the City Jails, Bilibid Prison and the ECQ offenders. These are communities that consist of 1000 families or a population of 4000 persons. The houses of the informal settlers do not even comply with the 2-meter spacing. Just imagine if these communities are infected. Immediately the curves will spike uncontrollably. Consequently, the health system is jeopardized. Then we revert to Case 1 or “back-to-zero”. It is going to be a cycle that will damage our economy.
  • Moving 75 % the informal settlers in Metro Manila to Subic or to provinces where they are welcomed. Like a “Balik-Probinsya Muna” Program. To be more aggressive, the informal settlers will be beneficial of an “On-site Housing Program”.
  1. Similarly, the prison settlers be transferred to other jails outside Metro Manila. The news today registered CODIV-19 infected prison settlers.
  • The commercial activity in wet markets or palengke should be reduced to 50%. Social spacing should be mandatory.
  • The OFW and balik-bayans should be strictly quarantined for more than 15 days.
  • Recommendation for May 1, 2020

The news today was that several health workers was infected. Also, in today’s news at least 45 inmates in Cebu was infected by CODIV-19. All these adds to total number of infected CODIV-19. These indicates that the most exposed and vulnerable are being infected. My suggestion is to focus on the April 27, 2020 recommendation.

5.0 Recommendation for May 5, 2020

As part of the April 27, 2020 recommendation, I would recommend the government to make a request to the US government to have access to the drug Remdesivir being processed by Gilead Science which is now distributed free at this time. This drug reduces the time an infected person is cured of CODIV-19 in 5 to 11 days. This drug is significant because it will increase recoveries that would “flatten the curve” towards a downtrend curve; provided the government strongly implement the recommendation last April 27, 2020.

Also, it is recommendable for the informal settlers be relocated immediately to such areas as Subic on the condition that their present homes in the cities will be upgraded to a decent home for a family. Please note that Subic is almost as big as Singapore and the US Navy has left many housing or covered facilities that can temporarily house the informal settlers.

Also, the government “Balik-Probinsya” Program should be given priority. The incentive is to earn the same income they get from urban cities and life of the settlers is much better in the provinces. Otherwise, they will return to the cities.

 To answer the first question and to conclude, the government does not have  

 the capabilities to solve the Covid-19 Pandemic. Good luck to Us and Stay safe.

       [ Also, refer to my earlier Article “ Bending the Flattening the Curve” ]

Report Prepared By;

Fernando S. Guevara

fernando@gpiengineers.com

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