Categories
Best Practices

Malaysia’s Response to COVID-19: The Full Official Account

The Ministry of Health Malaysia, via the National Institutes of Health (NIH) Malaysia has released an official account on how the country coped with the COVID-19 pandemic during key months of January up to April 2020. It takes the reader through a detailed chronology of what happened behind the scenes and the actions the Government of Malaysia had to undertake to curb the spread of the virus as events slowly unfolded in the country and the world.

This account hopes to be able to shed light into the learnings that can be gleaned from Malaysia’s own experience in its ongoing battle to contain COVID19. Currently, Malaysia remains amongst the top countries in the world in COVID19 recovery.

However, the Government of Malaysia is not taking its success for granted and recognises that the fight is far from over. The authorities are actively monitoring the situation and progressively deciding on whether further actions may need to be taken to maintain the successful containment of COVID19.

The full 164-page report is viewable at the following link.

Credit: Institute for Health Systems Research, National Institutes of Health (NIH) Malaysia

Categories
Best Practices

Global Pathfinder Report Preview now live with Full 122-Page Report Launch on 6th August 2020

The effects of the global COVID-19 pandemic look likely to remain with us for some time to come. While some countries are through their initial peak, many are still in the midst of their critical response to the health crisis.

As countries have taken varied responses to manage COVID-19, PEMANDU Associates and Delivery Associates have collected the practices of 20 countries that have maintained a strong recovery index in the fight against COVID-19. These early insights could prove critical as countries look to learn what works in response to the pandemic.

Read our summary report now, with the full-length report scheduled for publication on 6 August.

You can find the link of the microsite here and may download the summary report at this link.

Categories
GCI Updates

The GCI Recovery Index now applies derived Active Cases formula for Netherlands and United Kingdom

We are pleased to update that we have included a method to derive the Active Cases and by extension Recoveries for both Netherlands and United Kingdom. Both these datasets currently are not recorded by Johns Hopkins University and many other data aggregators.

For the Netherlands, the information that has been used as a proxy for Active Cases is the “Estimated Number of Infectious People in Netherlands” (Geschat aantal besmettelijke mensen in Nederland) which is published by the Government of the Netherlands on their COVID19 dashboard. This data will be manually updated in our database as and when it becomes available. By virtue of its inclusion, the GCI will also now derive the estimated recoveries nett from confirmed cases and COVID19 deaths.

For the United Kingdom, we have recognised that the UK Government keeps regular track of the number of individuals currently still hospitalised due to COVID19. We have also made reference to the World Health Organisation Report (Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19)) dated February 2020, which indicates that “…the median time from onset to clinical recovery for mild cases is approximately 2 weeks and is 3-6 weeks for patients with severe or critical disease.” For the purpose of the GCI recovery index calculations, we have taken the sum of 3 weeks of new cases and the latest reported total of hospitalised COVID19 patients (the latter as a representative of severe cases).

This new calculation method will be applied from 27th July onwards to the GCI Recovery Index scores but will not be retrospectively updated.

We hope that with this methodology update, the data for both the Netherlands and United Kingdom will better represent the efforts the respective Governments are currently undertaking in their efforts to battle this pandemic.

Categories
Research Excerpts

Lower Case-Fatality Rates for Economic Blocks which have both High Ambient Temperatures and Low Latitude

Sunway University has identified that countries that possess both high ambient temperatures and low latitudes have low COVID-19 Case Fatality rates. These findings appear to support epidemiological hypothesis that temperatures do play a role in managing the impact COVID-19 may have, particularly on mortality rates.

Excerpt from Sunway University:

We started by applying SARS-coronavirus 2 (SARS-CoV2) as the causative agent of COVID-19. It has been suggested that high ambient temperature disfavours coronavirus infection. This is supported by two lines of evidence:

  1. Elevated surface temperatures reduces viral viability;
  2. Infectivity of coronavirus decreases towards deeper, hotter airways.

Thus the question arises, ‘Can high ambient temperature limit the number of fatalities in COVID-19 cases?

Case-fatality, ambient temperatures and the latitude of 184 economic blocks were retrieved on 21 May 2020. After excluding 123 of those blocks with fewer than 2,000 confirmed cases, we proceeded with analysis of the remaining 83 economic blocks. We calculated case-fatality has by taking the total number of deaths divided by the total number of confirmed cases.

Figure 1. Influence of ambient temperature and latitude on case-fatality

Case-fatality was divided into four groups:
• 0-2%
• >2-4%
• >4%-8%
• >8%

We analysed the average monthly lowest and highest temperatures from the month of which the first confirmed case-fatality case(s) were reported through to May 2020. Because of the very high case-fatality observed in a number of European countries including Belgium, France and the United Kingdom, we also looked at the association between latitude and case-fatality. Kruskal Wallis Test analysis has revealed the average monthly ambient temperature (lowest, P = 0.025; highest, P = 0.001) to be inversely associated with case-fatality, whereas conversely latitude is seen to be directly associated with case-fatality (P = 0.037) (Figure 1).

In simpler terms, we found a correlation that the case fatality rates were highest in areas of lower mean temperatures and higher latitudes, whilst the inverse can be noted in countries that have higher meant temperatures and lower latitudes (i.e. closer to the Equator).

We found this to be a key insight and Sunway University are looking to find other unique correlations that could be gleaned from looking at COVID-19 using a data-driven approach.

Credit to: Dr Chook Jack Bee, Prof David Bradley, Prof Peh Suat Cheng from School of Healthcare and Medical Science, Sunway University; and Dr Jane Teh Kimm Lii and Prof Teo Kok Lay from School of Mathematical Science, Sunway University

Categories
Research Excerpts

Fourteen unique COVID-19 trend groupings identified by Sunway University following analysis on confirmed cases of 184 economic blocks

Using the Global COVID-19 Index (GCI) model as a supporting data engine, Sunway University has identified a unique way of looking at the spread of COVID-19 which it hopes to unveil new insights into country-level epidemic management. Via a dendogram analysis which takes into consideration multivariate factors, the researchers at Sunway University have identified 14 unique trend groupings from the 156 countries covered by the GCI.

Research Excerpt from Sunway University:

We attempted to study the trends of the first 60-day cumulative confirmed cases of COVID-19. We started by looking at the full sample set available from the GCI. After filtering out economic blocks with incomplete data and total confirmed cases fewer than 50 within the first 60 days, we proceeded to perform cluster analysis on 156 economic blocks.

A 5-day gradient was calculated for the cumulative confirmed cases of COVID-19. We then utilised a Hierarchical Clustering (Average Linkage) algorithm to construct a dendrogram. From the dendrogram, we identified 14 distinct clusters of countries that showed similar distribution trends of cumulative confirmed cases (Table 1).

These clusters cover a total of 58 economic blocks (38% of the filtered sample size). The remaining 98 blocks like China and Norway have standalone trends which potentially can be case studies of their own.

It will be interesting to see if the observed epidemic management of economic blocks within the same cluster share commonalities that could lead to greater insights as to what caused these trends to be similar. We hope to use these findings to enable data-driven research from a different perspective to the more commonly explored parameters of regional, cultural, income, healthcare systems and population density. Of particular interest would be the measures undertaken or not undertaken to contain the spread of COVID-19.

Table 1. Distribution trends of cumulative confirmed cases of COVID-19

Credit to: Dr Chook Jack Bee, Prof David Bradley, Prof Peh Suat Cheng from School of Healthcare and Medical Science, Sunway University; and Dr Jane Teh Kimm Lii and Prof Teo Kok Lay from School of Mathematical Science, Sunway University