[ANALYSIS] There’s still much work to do to curb this virus in the PH

Joseph Anthony Lim
'We are victims of the long-run neglect in the health and hospital systems of the country'


Table 1 below compares the Philippines with 23 other East and South Asian countries. 

1. Testing capacity

One can see in the last column of Table 1 that the number of tests per 1 million population is still low. As of May 20, 5:32 GMT, the Philippines is doing around 2,237 tests per million population, lower than poorer countries like Vietnam, Nepal, and Bhutan.

Testing capacity was increased in designated laboratories, using Real-Time Polymerise Chain Reaction (RT-PCR) testing, a swab test which detects the genetic information of the virus. The other tests are mostly approved rapid test kits which detect antibodies against COVID-19 or the presence of the COVID-19 virus in the blood. The rapid tests have a higher percentage of error, around 15% up. Thus, the official cases reported are only those from the laboratories using RT-PCR tests. As of May 15, there were 30 RT-PCR laboratories in the country. (READ: How poor is the Philippine health system? Many hospitals not qualified to test for coronavirus)

Last week, a team of UP experts revealed they found several errors in recordings and delayed transmission of test results. Around the same time, Dr Benjamin Go revealed that in his compilation and monitoring work, he found that test results, ideally revealed within 48 hours, actually took 3 to 14 days. His followers found that 114 deaths released between May 6 to May 12 were deaths 21 days earlier on the average. 

These delays and errors affect tremendously the accuracy of the doubling-time analysis as to whether the number of days, cases, and deaths are becoming longer, a sign of curve-flattening. There is no clear plan or strategy, however, by DOH to tackle this grave data problem. (READ: Duque on data errors: ‘Less than 1%, doesn’t affect decision-making’)

Table 1

Philippines Covid Statistics Compared to the East and South Asian Countries for May 20, 2020, 05:32 GMT

World RankCountryTotal CasesTot Cases/1M popDeaths/1M popCase Mortality RateCase Recovery RateTotal TestsTests/1M pop
  World 4,989,061 640 41.7        
11 India 106,886 78 2.4 3.1 39.6 2,512,388 1,823
13 China 82,965 58 3.2 5.6 94.3    
19 Pakistan 45,898 208 4.5 2.1 28.5 414,254 1,880
27 Singapore 28,794 4,926 3.8 0.1 36 246,254 42,131
28 Bangladesh 25,121 153 2.2 1.5 19.9 193,645 1,177
33 Indonesia 18,496 68 4.5 6.6 24.2 202,936 743
39 Japan 16,367 129 6.1 4.7 70.7 255,675 2,021
43 Philippines 12,942 118 7.7 6.5 22 244,800 2,237
44 S. Korea 11,110 217 5.1 2.4 90.6 776,433 15,146
56 Malaysia 6,978 216 3.5 1.6 80.9 462,257 14,304
70 Thailand 3,033 43 0.8 1.8 94.2 286,008 4,099
98 Maldives 1,143 2,119 7.4 0.3 8 11,775 21,830
99 Hong Kong 1,056 141 0.5 0.4 97.1 168,291 22,469
102 Sri Lanka 1,027 48 0.4 0.9 55.4 46,413 2,169
130 Taiwan 440 18 0.3 1.6 91.1 69,395 2,914
132 Nepal 402 14 0.1 0.5 9.2 107,253 3,689
142 Vietnam 324 3 0 0 81.2 275,000 2,828
151 Myanmar 193 4 0.1 3.1 53.9 15,137 278
158 Brunei 141 323 2.3 0.7 96.5 17,636 40,358
159 Mongolia 140 43 0 0 18.6 11,641 3,558
164 Cambodia 122 7 0 0 100 15,572 933
179 Macao 45 69 0 0 100    
188 Bhutan 21 27 0 0 23.8 14,294 18,549
189 Laos 19 3 0 0 73.7 4,653 641

Source: Coronavirus Updates, Worldometers

2. Contact tracing

To avoid infections and mortalities, contact tracing must go hand in hand with massive and fast testing. The World Health Organization (WHO) has pinpointed the major bottleneck in contact tracing as the availability of timely and complete information from COVID patients of hospitals and quarantine centers. LGUs will also have to be active in tracing and testing persons under investigation (PUIs). Secretary of Finance Dominguez, cognizant of the need to strengthen contact tracing, had proposed that the unemployed be temporarily hired to assist in contact tracing activities, but, so far, there has not been any clear action plan on this proposition. (READ: Salceda fears second wave, cites poor contact tracing and testing)

3. Analyzing the results of cases, mortality, and recoveries

Going back to Table 1, we see that the Philippines, by May 20, had a total of 12,942 COVID-19 cases, amounting to 118 COVID cases per 1 million population. This is more in the middle to lower end among the countries in the table. However, the Philippines has a relatively low number of tests per million people, so it is expected that the number of cases per million people will be understated compared to countries which have done massive testing.

Looking at both the mortalities per 1 million population and the case mortality rate (the mortality rate among the cases detected), the Philippines has the worst mortality per 1 million population (7.7) among the countries in Table 1. Together with Indonesia, it also has the worst case mortality rate at 6.5% among the total cases detected. It also has one of the lowest case recovery rates among the countries at 22%, joining the ranks of the poorer countries in Table 1.

The high mortality rate and low recovery rate for sure have to do with the poor health and hospital care, equipment, and infrastructure in the Philippines, as well as lack of hospital staff to attend to the many patients. Also contributing to this will be the original low number and late testing among the population and poor contact tracing. These latter elements could have prevented many infections. WHO reports that between January 18 and May 13, senior citizens made up 68% of COVID deaths.

4. Slow start and underutilization of out-of-hospital quarantine facilities 

Another worrisome problem in the DOH is the slow process in achieving the full operation of out-of-hospital quarantine and treatment facilities, which can house and isolate COVID patients exhibiting mild or no symptoms so that they will not infect others. This may be due to lack of contact tracing as well as shortages in personnel and equipment. WHO shows that patients accommodated in off-hospital quarantine facilities and treatment centers are far below their bed capacities.

5. High mortality rate among health workers: The unsolved problems of understaffing and PPEs

The COVID infection rate of health workers in the Philippines remains one of the highest in the world – 18% in May 19. This comprises more than 2,300 health workers. They are comprised roughly: 40.7% nurses, 32.5% doctors, 7% nursing assistants, 6.1% medical and radiology technologists, and 13.7% non-medical staff. As of May 19, 35 health workers had also died of COVID-19 – more than two-thirds were medical doctors, and the rest were nurses. 

Understaffing of hospitals and health centers as well as shortages of quality PPEs are the main causes of these infections and deaths. Many hospitals and quarantine centers have requested DOH for additional health personnel. The government has an ambitiously announced program of domestic designing and production of PPEs contracted with CONWEP (Confederation of Wearable Exporters of the Philippines). So far this has not been very successful. Health workers have to wear their PPEs and masks repeatedly, reducing the safety standards. Now, more and more PPEs are being imported or donated from abroad.

6. Towards a long-run “new normal” for health

We are victims of the long-run neglect in the health and hospital systems of the country. The many infections and deaths, as well as overworked and exposed health workers, are a result of poor health infrastructure and health personnel policies, which see many underpaid health workers seeking jobs abroad. For our “new normal,” it is imperative that the government tackle these problems in the urban and rural areas. The COVID-19 pandemic has shown us our weaknesses in infrastructure, personnel, and health governance in the urban sectors. One dreads to imagine if the pandemic reaches the poor rural areas as well. – Rappler.com

Joseph Anthony Y. Lim is a Professor of Economics at the Ateneo de Manila University. He is also a retired Professor of the School of Economics, University of the Philippines, Diliman. He took his master’s in Operations Research at the Massachusetts Institute of Technology (MIT) and his PhD degree in economics at the University of Pennsylvania. He was a poverty adviser for Bureau of Development Policy of UNDP in New York 2002-2004. His research work includes macroeconomic issues of the Philippines and Asian economies as well as economic development concerns of third world countries.