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April

2020

Evaluating the Reliability of the Number of Confirmed Covid-19 Cases Reported by Various Countries

by Khairul Omar for Young Digital Leaders

Working assumptions

It can be hard to gauge the true extent of the spread of Covid-19 outbreak in each country since different countries have different resources and policies in conducting tests. In comparison, the number of deaths caused by the virus are more likely to be reported correctly as seriously ill individuals would seek medical attention, plus more rigorous reporting procedures in recording such cases.

Under-reported official positive cases from around the world can be caused by missing cases related to positive individuals who are asymptomatic and those who recovered at home without being tested. Low official figures can also be attributed to delays in reporting due to poor laboratory capabilities and other logistics issues.

Evaluation methodology

Data for the number of Covid-19 deaths were gathered from John Hopkins University while the number of tests were derived from Our World in Data database. In both cases, data is compiled using official government sources and press releases.

By plotting the number of deaths vs. the number of confirmed cases and the number of tests performed, we ran linear regression models to find the relationship between the measures in question. Countries that lie close to or above the regression line can be interpreted as being more likely to have adequate testing and reporting policies when comparing to other countries with similar severity, as measured in the number of deaths. On the contrary, a given country can be interpreted as being more likely to have inadequate testing and reporting policies if it lies further away below the regression line.

We wish to emphasise that while this method may not be a guaranteed way in assessing the reliability of official figures by country, it could provide a guide in benchmarking a given country’s policies versus other comparable countries. Please exercise caution in interpreting the results as there may be other underlying factors at play that may not considered in the model.

Are reported cases under-estimated?

In the analysing the number deaths versus the number of official positive cases, the area shaded in orange can be interpreted as countries where the official number of confirmed cases are more likely to be under-reported due to various reasons. Based on this method, we may have reasons to believe that the number of total cases reported for Malaysia so far can be used to represent the actual situation on the ground, especially when comparing with other countries with almost similar number of deaths such as Hungary and Ukraine.

Are countries testing enough?

We can also benchmark if Malaysia is testing enough by looking at how other countries are performing. Similarly, as in the analysis above, we shall use the number of deaths to gauge the spread of the virus in the population instead of using the official confirmed cases figures. Using a regression line to find a relationship between the two, we can interpret that countries that lie below the line in the shaded area are more likely to be under-testing its population. South Korea and Germany, which have been praised by the WHO for their testing policies, are well above the regression line.

The Clarifying Role of Epidemiology – How to Interpret Demographic Visualisations

The above graph has been making it’s rounds on the internet over the last week. It highlights the distribution of COVID-19 cases in Malaysia.  As simplistic as they seem, graphs such as these can inform the ascertainment of high-risk populations, and direct control activities such as screening of populations. All visualisations have caveats, and the plot above is no different. Epidemiological intuition in interpretation of such graphs can provide us some insight into the bad, the nit-picky and the good of such visuals. We explore these themes below.

The Bad

First and foremost, the issue with the above bar-plot is that it reports case counts in identifying groups that are most numerous in testing positive. In epidemiology (and common-sense), frequency of any state should be presented as a ratio, using a denominator common to all comparator groups. In epidemiology, one such metric is the incidence ratio- which is the fraction of new cases (in a particular group) over the total population. This would provide us with the true ratio of positive cases in a particular group of people. As can be seen below, the incidence ratio gives a far clearly picture of test postive numbers by age groups. This picture is also far more consistent with what we know (as of know) with regards to patterns of symptoms by age groups- as clinical manifestation appear more in older groups  (Mizumoto, Kagaya, Zarebski, & Chowell, 2020).This in turn appears to  directly mediate the yield of positive screening test numbers (Wang et al., 2020). Benchmarking on age-related data from other similarly affected coutries will likely provide a clearer picture of this .

The Nit-Picky

Interval classes. The choice of interval classes, is heavily subjective- and is generally left to the best sense of the data analyst, epidemiologist, statistician, scientist etc. However, the use of ‘non-standard’ age groups makes the development of composite ratios, such as the incidence rate above, very challenging. Age-group data from public datasets such as the census can be rendered useless as the comparison of mid-year populations in these public datasets use a standard interval of “0-4,5-9,10-14..etc” whilst the above uses a interval class of “1-5, 6-10, 11-15…etc”. The difference may not look like much, but it makes any further use difficult- and renders graphs such as the one above a mere approximation that is susceptible to error.

The Good

However, despite the critique, there are important reasons why the graph did highlight something very important. This is illustrated in the graph below: a comparison of population counts by age group and positive tests by age group.

Here we visualise something very interesting, the population distribution (in pink) grants clues regarding populations with particularly low rates of positive tests. There are two possibilities that can exist within this hidden population:

  1. They have not been tested.
  2. They have tested negative.

The implications of either possibility are important. If this population has not been tested, then the low-cumulative positive test rates observed (~3% over the last 4 days, average remains ~7%), is a signal for the surveillance system to increase its sensitivity in screening. One possible action is for the screening machinery to focus on individuals within these age-groups instead.

The implications of the second though are more complicated. High rates of negative tests would mean high rates of false negatives- which in turn would signal (perhaps) the need to reformulate the current screening protocol- which of course is not an easy task considering the lack of scalable alternatives currently. This of course also highlight the issue of false negatives- which have been informally reported to be as high as 30% (Lanese, 2020). However, with no systematic analysis into the use of the rt-PCR [1] as screening- we maybe for the present moment- incapable of detecting this “hidden population”.

It is important to note that the trail of data ended at one simple graph, with no connectors. It is therefore near impossible to extrapolate possible improvements that can be made via such limited data. The take home here is succinct – In this war we fight together, never has open data been more relevant than today.

References

Lanese, N. (2020). Even if you test negative for COVID-19, assume you have it, experts say | Live Science. LiveScience.

Mizumoto, K., Kagaya, K., Zarebski, A., & Chowell, G. (2020). Estimating the asymptomatic proportion of coronavirus disease 2019 (COVID-19) cases on board the Diamond Princess cruise ship, Yokohama, Japan, 2020. Eurosurveillance, 25(10), 2000180. https://doi.org/10.2807/1560-7917.ES.2020.25.10.2000180

Wang, W., Xu, Y., Gao, R., Lu, R., Han, K., Wu, G., & Tan, W. (2020). Detection of SARS-CoV-2 in Different Types of Clinical Specimens. JAMA – Journal of the American Medical Association. https://doi.org/10.1001/jama.2020.3786


[1] Reverse Transcriptase Polymerase Chain Reaction

Benchmarking government response on Covid-19 in Malaysia vs. key countries

by Khairul Omar for Young Digital Leaders

As Malaysia heads into its third week of Movement Restriction Order (MCO), we seek to study how the lockdown is impacting the number of confirmed Covid-19 cases and to compare various performance measures with other countries. University of Oxford is currently the leading authority in tracking government responses from around the world in handling the crisis under its OxCGRT data repository. Based on multiple responsive measures such as movement restrictions, contact tracing and testing policy, OxCGRT generates a stringency index as a measure to rank countries on how strict the government policies are, which is updated daily.

Tables above is a summary of the latest scoring for each response category for Malaysia and other countries by OxCGRT, with the stringency index between 0 to 100 displayed next to the country name. Malaysian government responses are currently ranked at the lower end of the upper tier with an index of 71.0, although there are more improvements to be carried out particularly in ramping up tests and formulating a more effective contact tracing procedure. The latter is particularly important when the time comes for MCO to be eased or lifted in order to avoid a second outbreak, which is currently carried out by South Korea to keep its level of new cases at a relatively low and fairly constant level after the initial peak.

As new government measures are introduced, the stringency index is updated to reflect the latest ranking on how each country handles the crisis. The two charts below, each for comparing Malaysia with Asia-Pacific countries and the West, are useful in analysing how different governments reacted, particularly in identifying if there have been lost opportunities that could have been implemented earlier and how countries can learn from each other ahead of time.

Using data from John Hopkins University Coronavirus Resource Centre, we shall explore how the number of confirmed cases has changed since the lockdown by comparing the situation in Malaysia with other key countries in the Asia-Pacific region and in the West. As most countries in the analysis have completed nearly three weeks of lockdown, we are currently in a good position to conclude that most if not all countries are a seeing a drop in the exponential growth of the total confirmed cases thanks to social distancing which reduces the basic reproductive number (R0), namely the number of people that each positive person can infect. Looking at the situation in Malaysia, if the growth rate at the start of the lockdown remained unchanged, it would lead to the doubling of the number of total cases in 4 days compared to around 2 weeks after three weeks into the lockdown.

Looking at the impact on the growth factor alone does not paint the full picture into the severity of the crisis. Despite all the signs that total cases are growing at a slower rate, countries that started off with a very high number of cases continue to see a large numbers of daily new cases due to the exponential nature of the pandemic which would take more time to taper off into much lower levels. The chart below shows how the number of new cases has changed in relative to situation at the start of lockdown (set at an index of 100) which is useful in comparing countries where the number of cases is several orders of magnitude different. Note that only countries that have gone through at least a week of lockdown are shown the analysis below.

Austria and Switzerland may well have had their worst behind them and are already planning on easing some of the toughest restrictions in the coming weeks. Italy and Spain are also showing signs that recovery is under way after three weeks of lockdown, but it is not entirely clear if the same could be concluded for the United Kingdom and Canada just yet.

The trend in the number of new cases in Malaysia is still inconclusive for now as it appears that there is no clear sign yet that the level is going down or worsening, as it now hovers around 165 new cases mark for the past two weeks. It is hoped that the ongoing measures will bring the number of new cases further down before plans for easing the restrictions could be considered.

An overview of global fiscal responses to COVID-19 pandemic

by Najlaa Ramli for Young Digital Leaders

Overview

Earlier in March 2020, International Monetary Fund (IMF) has recommended priority areas in which the government must uphold in the time of COVID-19 pandemic. The mentioned areas are:

  1. Prevention of people from contracting the disease, containment & suppression of the disease, and treatment to those who are affected;
  2. Provide timely, targeted and temporary cash flow relief to those who are most vulnerable/affected in the time of crisis; and
  3. Prepare a protection and continuity plan for individuals and businesses during the crisis and easing out afterward.

The priority of every government is to protect the wellbeing of its people. In facing the serious global pandemic crisis, governments around the world are reacting to limit the human and economic impacts of the COVID-19 outbreak. Here is an overview of the magnitude of fiscal measures that have been announced by some governments so far:

Picture 1 Source: IMF, government announcements of stimulus packages

Following the surge of positive cases of COVID-19 recorded worldwide, governments started announcing their intervention measures. Whilst containment and suppression measures via social distancing and lockdown are deployed, fiscal policies or government’s spending and tax instruments are being expanded.

Taking the amount of fiscal stimulus as a percentage of a country’s GDP, Malaysia seems at the forefront at over 15%. Prihatin Economic Stimulus Package (ESP) announced on 27 March 2020, altogether with an economic stimulus package for vulnerable sectors announced earlier in late February, fiscal stimulus package in Malaysia amounted to RM250 billion (~US$58 billion).

However, it is too premature to claim the interventions taken by our country are either enough, or effective. Other governments are also reacting to the crisis actively by continuously reviewing and preparing for additional stimulus as the situation needed. For example, Singapore initially announced its fiscal package to deal with economic slowdown on 18 February 2020. A supplementary budget was announced on 26 March 2020 that includes the expansion of subsidies and cash payouts to households. United States of America (USA) also has announced its stimulus package in three phases since early March.

Healthcare expenditure: A Priority during public health crisis

COVID-19 pandemic is first and foremost a public health crisis. Hence, the priority of government responses should lie on health care systems to contain and suppress the outbreak. In the absence of medical countermeasure such as vaccines, the alternative approach involves rigorous testing, treatments for all infected patients, readiness of intensive care units, and adequate support to healthcare workers.

In general, all healthcare systems are undergoing capacity constraints during the outbreak. The existing number of hospital beds and intensive care units will not be sufficient with the spread of the outbreak. The stockpile of medical gear, such as ventilators, medicines, and personal protective equipment (PPE), are depleting. Additionally, support and protection for frontline healthcare staff are essential in tackling the outbreak.

Picture 2Source: IMF, government announcements of stimulus packages

Hong Kong allocated about HK$30 billion or 1 percent of its GDP for its newly created Anti-Epidemic Fund. The allocation is to provide additional resources to its Hospital Authority and sufficient protection for frontline healthcare staff. Hong Kong is allocating the fund for the deployment of additional manpower, procurement of additional PPE and other services related to medical, such as for cleaning, security, transportation, storage, clinical waste disposal, and hospital supplies.

Social aid: Cushioning the economic shocks and uncertainties

COVID-19’s containment and suppression measures require some degree of social distancing and movement restrictions of the general public. The trade-off from this measure is curtailed economic activities that introduce shocks to supply and demand in the economy.

It is also a task on hand for the government to cushion the impact of the inevitable economic fallout and ensure proper measures are prepared for the subsequent need to get the economy up and running again. Heightened uncertainties during this crisis lead to a drop in consumption and investment, in which it triggers a chain reaction that worries the household and businesses.

Picture 3Source: IMF, government announcements of stimulus packages

For households, objective of fiscal policy should be focusing on income support, especially during the quarantine or in the time of temporary laid-off. Households who are considered as the more vulnerable group are those dependent on daily wages, who have low income, disabled and homeless people. Many households are also expected to be on temporary unemployment because of the COVID-19 shock. Social assistance ranging from cash transfers, discounts, or unemployment insurance are amongst the temporary support that can be offered by governments to protect their distressed populations from the economic repercussions of COVID-19 crisis. In general, most governments are providing and delivering this assistance for the next three to six months for their resident, with the hope that the pandemic situation will ease out soon.

For businesses, their concern is having adequate cash flows to pay workers and suppliers. Tax relief, subsidies, deferment of loan payment, flexibility in lending to small and medium-sized enterprises and credit guarantees are amongst offer that government may present as options.

Australia has announced several stimulus packages in March 2020. They started with an announcement of wage subsidies for businesses. Subsequent measures include payments to jobseekers and payment for employers to pass on to employees for them to stay in work. Reserve Bank of Australia also announced a three-year funding facility to help banks continue to lend to businesses.

Expect evolving reactions from the governments

Unprecedented interventions by the governments at this junction are needed, without a doubt. Under this COVID-19 circumstance, governments are actively figuring and accommodating to their best to cushion the impact of this health emergency and economic downturn. Enhancements to stimulus packages are being announced as we navigate through this unprecedented crisis. Ambitious interventions to mitigate this episode are important for everyone – young and old, low and high income, individuals and businesses.

The impact of Covid-19 lockdown by key countries

by Khairul Omar for Young Digital Leaders

Benchmarking against China’s success story

China is the only major country that has managed to bring down the number of new cases to very low levels based on official figures. This was achieved by a strict implementation of lockdown that went beyond the level practiced in Europe and elsewhere. Lockdown was only eased 60 days after it was first imposed, at the time when the number of new cases were practically zero. In fact, near-zero level (both in terms of new cases and day-on-day growth) was achieved around 2 weeks prior to the easing of the lockdown, but the strict measures remained intact.

Based on the lessons learned from China, it would be premature for other countries to lift movement restrictions currently in place until the benchmark seen in China has been reached in order to avoid future outbreaks. While the strictest form of lockdown has been lifted in China, many other measures are still in place there until the government is confident that the outbreak is truly behind them.

South Korea: containment without lockdown

South Korea managed to control its outbreak through containment and contract tracing without the need for lockdown measures. While this analysis focuses on the impact on movement restriction, it would be beneficial to study how the outbreak phases panned out in South Korea and what other countries can learn from it.

Also note that unlike China where new cases tend to hover around a single or two-digit, South Korea to date stabilizes at around 100-case mark which it will continue to manage in preventing it from exploding to a new peak. This may well be the outcome for other countries, which further suggests the importance of continuous efforts to contain the spread and not to let our guards down when the worse may appear to be behind us.

Countries currently under movement restrictions

While the United States is the worst-affected country to date, there is still limited timeframe available to analyse its lockdown impact as the country continues to exponentially grow in new cases. Therefore, we shall not be looking at the United States for comparison and focused our benchmark towards 4 key European countries with nationwide restrictions.

Italy, once the worst-hit country behind China during its peak, have started to show positive signs from the lockdown around 3 to 4 weeks after it was first implemented in the north. With the latest day-on-day exponential growth at around 5% and total case of over 115,000 as of Apr 2, the number will still continue to rise in large numbers, but it does seem to be moving in the right direction towards a gradual recovery.

Spain seems to be around one or two weeks behind Italy in terms of the pace of recovery. There appears to be a first sign of a shift in the past few days but it may still be early to conclude that the nationwide State of Alarm is driving total cases down. France is in their third week of lockdown where the first sign of a turn may be on the horizon as in the case of Spain, but more time is needed before an fair assessment can be made.

United Kingdom is relatively behind in imposing a strict movement restriction. After nearly two weeks of implementation, an upward trend in daily cases with an exponential growth of above 13% is still being observed. As in the case of its neighbouring countries, it may take another week or two before the first signs of a positive effect could be observed.

Malaysia is currently in the second week of Movement Control Order (MCO). Although it appears that the number of new cases is heading towards a stabilizing trend instead of going upwards, more time is needed to assess if the restrictions imposed by the government are having a significant impact on the number of new cases. A continuous downward trend and a flattening in new cases needs to be sustained for a substantial amount of time before the movement restrictions can be loosened or lifted.