Covid Malaysia - Numbers

Update on Covid Outbreak in Malaysia

Dr. Wan M Hasni, Chief Data Scientist (Techna Analytics Sdn. Bhd., Malaysia)

Table of Contents


Today (March 20) is the 80th day of Covid-19 (start date is December 31st, 2019) global pandemic; The starting date for measurement that we will use is days from the first threshold of 100 confirmed cases. Malaysia is 8 days from the first threshold, China is 56 days, South Korea is 55 days, Italy is 20 days, and Singapore is 16 days.

The days from the first threshold is important in comparing various metrics between countries, to provide indicators of how a country fare compared to others in terms of the state of the pandemic, at a country level.

Key metrics we will attempt to monitor are as follows:

  1. The rate of growth of confirmed cases
  2. The number of tests conducted
  3. Timeline and time factors (lead-lags)
  4. Significant events

There are other important metrics, but not covered in this report due to lacking data/information and domain knowledge (especially medical expertise). Other metrics are critical such as the distribution of healthcare facilities dedicated to testing and post-detection care, lead-time for test results and accuracy of testing and others. We do not have any means to obtain these data.

Growth rates of confirmed cases

The growth rate is assumed to follow exponent based scale-free statistical distribution, measured in terms of how many days for confirmed cases to double. The bursting nature of any pandemic generally demonstrates an early stage of the extremely fast growth of doubling every day, and if left unchecked the rate will even grow even steeper (i.e. increasing rate of the rate of growth). The first step is to ensure that this growth rate stops its increment (i.e. flatten the growth rate), then thereafter to eventually decrease to zero. It is important to analyze this metric, instead of comparisons based on the number of cases per se. Furthermore, we need to observe whether this growth trajectory follows or differ from country to country, and from one stage (days from the start) to another.

The growth rate estimate is rather coarse (large variations of range), mainly due to: a) the pathogen has quite a long period of incubation (i.e. infected person may not show any symptoms until 7 days and could be as long as 21 days), b) under-reporting or misreporting by healthcare agencies, and c) the nature of human mixing behavior (heterogeneity and levels) at different stages of the disease control process.

Based on this background, let us have some ideas about the current state of the rate of growth of Covid-19 in terms of reported confirmed cases in Malaysia. (The number and estimates are based on our projections)

Days Benchmark Actual/Estimates Actual/Forecasted Cases
3 days past 1-3 days 1-2 days 197
2 days past 1-3 days 1-2 days 238
1 day past 1-3 days 1-2 days 553
Today 1-3 days 1-2 days 900
1 day forward 3-5 days 3-5 days 1100 - 1300
2 days forward 3-5 days 3-5 days 1300 - 1500
3 days forward 3-5 days 3-5 days 1500 - 1700
beyond 3 days 5-10 days 5-10 days N/A

Since today is day 2 of MCO (Movement Control Order), the effect of slowing down of growth rate is expected to show its full effects probably after 3 to 7 days from the start date. The key factor that we have to observe is what would be the actual growth rates for the next few days and beyond 3 days from today.

Note of caution: The estimates produced here are extremely coarse due to lack of granular (detailed) data which limits the modeling and rigorous statistical testing. Hence please take due care in interpreting the forecast provided; at best it could only serve as a benchmark/guide.

Number of testing conducted

Unfortunately, the number of tests conducted daily for Malaysia is not available. So far the only official data is for March 19, which is: 9,799 tests conducted. The number of tests conducted is an important indicator in terms of the ability of the healthcare system to cope with the outbreak, particularly for early detection which reduces the chance of further spreading by infected people.

We provide some indicators in the table below for comparisons:

Country No of Tests No of Cases Ratio of Test/Cases Tests per Million Population
Malaysia 9,799 900 10% 298
South Korea 286,716 8,320 3% 5,566
Italy 148,657 27,980 18% 2,514
UAE 125,000 98 0.01% 12,737
Japan 16,484 829 5% 130

Notable mentions:

  1. To be successful in containing the outbreak relies on the ratio of test/cases - whereby successful measure would be to bring testing numbers as large as possible (and hence ratio of test/cases to be as low as possible). A good benchmark is Korea and Japan (3% and 5% respectively). An extreme case is UAE which went for an extensive testing drive. Italy is a case where the need to even increase the tests (to reduce the ratio) is crucial.
  2. Another measure is the number of tests over the population at large (per capita), which can be seen from the cases of South Korea where the testing drive is extremely strong (beside UAE).

Why these metrics are important?

  1. Longer-term growth of the outbreak could be effectively controlled by having a strong testing drive. Testing is effective in preventing “bursting event”, where a sudden burst of a hidden element could be prevented or reduced.
  2. Reduction of spread or total elimination is possible if testing is intensified.
  3. It provides an indicator of the stresses the outbreak imposed on the healthcare system of a country.

Malaysia’s case requires attention to both the ratio of tests/cases and a much-needed boost on testing per capita. This could indicate many other hidden stresses on the overall system (healthcare and social behavior). Tracking of these metrics as the pandemic progresses is critical.

Timeline and significant events

There are two most significant events as of to-date:

  1. “Bursting” event of Sri Petaling Tabligh Ijtima’. Why the event is significant: a) In the network science terms, the event is a “burst” which cascades into a widespread infection of the pathogen; b) the event was a heterogeneous mixing of people which based on small-world property effectively could cause a single person to be in direct physical contact with literally everyone (5,000 to 10,000 people?) within the three days period. c) the event is a major node with significant hub property - which causes it to generate new nodes with hub properties - i.e. causes the pathogens to be spread across various regions of the country.

  2. Restricted movement (MCO) imposition. a) Based on data science, it is absolutely clear that it is necessary. The first rule is to reduce any forms of heterogeneous mixing of humans. However, the key point is to ensure or efforts must be made that the objective is to stop heterogeneous mixing, instead of any forms of mixing at all (which is impossible). The main purpose is to bring the probability of pathogen spreading to below a certain threshold (1% chance of spread) - and this requires an understanding of human mobility under a disaster - because it happens most of the time that confusion on rules imposed increased mobility and heterogenous mixing rather than reducing or stopping it. We saw some of these issues in the days prior to imposition, and lack of understanding of it, post imposition. For now, most of it is already events of the past. b) If the imposition is not backed by aggressive control of the disease by testing, the risk would be when the imposition is uplifted, whereby due to the incubation period of the pathogen, and a sudden rush of heterogeneous mixing thereafter could lead to future outbursts.


We will keep updating this updates to bring additional analysis besides tracking some of the metrics provided above, as more data/information becomes available.

May Allah protect us all.


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