COVID-19 - WHO South-East Asia Region - 20-08-06

Data from JHU, ca. 9:00 CET

WHO South-East Asia Region is a Group with the following members:
Bangladesh - Bhutan - Burma - India - Indonesia - Korea, North - Maldives - Nepal - Pakistan - Sri Lanka - Thailand - Timor-Leste

Go to the data tables

	absolute	cases per 100.000	abs. development 1 day	rel. development 1 day	rel. development 5 days/average
Total infections	2710430	121.6	68575	2.6%	2.38%
Active cases	775961	34.8	11915	1.56%	0.71%
Deaths	56606	2.5	1020	1.83%	1.43%
Recovered	1877863	84.3	55640	3.05%	2.39%

Deaths per infected	2.09%
Recovered per infected	69.28%
Active per infected	28.63%
Deaths per recovered	3.01%
Projection: Total Case Percentage	0.69%

	Last days rate	Last average rate
Gives the time necessary to double the existing infections - to reach a million from the existing status, or to reach the population limit of the given group (which can well be below a million). This assumes the exponential growrate of the last day or average of the last five days continues - which it does not, as there will be saturation towards the maximum. Please take these calulations with two grains of salt. As long as there is turning point in sight the data may well hold, though.
Time to double cases	27d 1h	29d 10h
Time to reach a million cases
Time to saturate the population	261d 22h	285d 2h

A ranking may taste a bit fishy, as this is not a competition between countries, but to compare the relative efficiency of measures taken, or for detecting which countries are likely to get critical next, this ranking imho deserves a place in this overview.
Total:	189	Population	na
	Total cases	Cases per 100.000	Average grow rate (5 days)
Infected	na	87	31
Active	na	71	69
Deaths	na	86	42
Recovered	na	82	34
The ranking is made over all groups and countries, including small or recent that are ommitted in the table on the front page - which may lead to minor discrepancies between both!

Diagrams

Members of Group: WHO South-East Asia Region

Bangladesh - Bhutan - Burma - India - Indonesia - Korea, North - Maldives - Nepal - Pakistan - Sri Lanka - Thailand - Timor-Leste

Data by Country

Click on the header to sort - Click on the name for the countries dashboard! - Only countries with more then 100 infections and more then 100.000 citizens are listed!

Click top row to sort:	±	±	±	±	±	±	±	±	±	±	±	±	±	±	±	±	±	±
Country	Pop (mio)	Infected	Active	Deaths	Recovered	Infected	Active	Deaths	Recovered	Infected	Deaths	Infected	Active	Deaths	Recovered	Deaths per Recovered		Recovered per infected
		absolute values				Percentage growthrate 5d				Time to double		Cases per 100.000				% / ratio
Pakistan	219.017	281863	19770	6035	256058	0.25	-3.46	0.21	0.57	272d 16h	328d 20h	128.7	9.0	2.8	116.9	2.4	1:42.4	0.91
Indonesia	266.912	118753	37587	5521	75645	1.55	0.38	0.98	1.7	44d 22h	71d 2h	44.5	14.1	2.1	28.3	7.3	1:13.7	0.64
Thailand	66.484	3330	124	58	3148	0.11	1.17	0.0	0.06	>1yr		5.0	0.2	0.1	4.7	1.8	1:54.3	0.95
India	1360.054	2027074	607384	41585	1378105	2.97	0.96	1.73	3.02	23d 15h	40d 10h	149.0	44.7	3.1	101.3	3.0	1:33.1	0.68
Sri Lanka	21.803	2839	287	11	2541	0.17	-4.14	0.0	0.8	>1yr		13.0	1.3	0.1	11.7	0.4	1:232.6	0.9
Bangladesh	168.304	249651	102521	3306	143824	0.8	0.23	0.85	0.8	86d 13h	82d 0h	148.3	60.9	2.0	85.5	2.3	1:43.5	0.58
Maldives	0.375	4680	1936	19	2725	3.46	7.35	2.29	0.68	20d 8h	30d 15h	1248.7	516.5	5.1	727.1	0.7	1:142.9	0.58
Bhutan	0.742	108	12	0	96	1.16	-1.54	0	0.89	60d 7h		14.6	1.6	0.0	12.9	0.0	na	0.89
Nepal	29.61	21750	6296	65	15389	1.61	2.21	1.4	0.9	43d 12h	49d 22h	73.5	21.3	0.2	52.0	0.4	1:238.1	0.71
Burma	68.67	357	43	6	308	0.23	-1.62	0.0	0.53	307d 6h		0.5	0.1	0.0	0.4	1.9	1:51.3	0.86
WHO South-East Asia Region	2228.78	2710430	775961	56606	1877863	2.38	0.71	1.43	2.39	29d 10h	48d 21h	121.6	34.8	2.5	84.3	3.0	1:33.2	0.69

More Data by Country

Click top row to sort:	±	±	±	±	±	±	±	±	±	±	±	±	±	±	±
Country	Pop (mio)	Infected	Active	Deaths	Recovered	Deaths per Recovered		Recovered per infected	Deaths per infected ... days ago					Possible Total %	Country
		absolute values				% / ratio		Recovered per infected	0d	5d	7d	10d	14d	Possible Total %
Pakistan	219.017	281863	19770	6035	256058	2.4	1:42.4	0.91	0.02	0.02	0.02	0.02	0.02	0.74	Pakistan
Indonesia	266.912	118753	37587	5521	75645	7.3	1:13.7	0.64	0.05	0.05	0.05	0.05	0.06	0.56	Indonesia
Thailand	66.484	3330	124	58	3148	1.8	1:54.3	0.95	0.02	0.02	0.02	0.02	0.02	0.02	Thailand
India	1360.054	2027074	607384	41585	1378105	3.0	1:33.1	0.68	0.02	0.02	0.02	0.03	0.03	0.83	India
Sri Lanka	21.803	2839	287	11	2541	0.4	1:232.6	0.9	0.0	0.0	0.0	0.0	0.0	0.01	Sri Lanka
Bangladesh	168.304	249651	102521	3306	143824	2.3	1:43.5	0.58	0.01	0.01	0.01	0.01	0.02	0.53	Bangladesh
Maldives	0.375	4680	1936	19	2725	0.7	1:142.9	0.58	0.0	0.0	0.0	0.01	0.01	1.37	Maldives
Bhutan	0.742	108	12	0	96	0.0	na	0.89	0.0	0.0	0.0	0.0	0.0	0.0	Bhutan
Nepal	29.61	21750	6296	65	15389	0.4	1:238.1	0.71	0.0	0.0	0.0	0.0	0.0	0.06	Nepal
Burma	68.67	357	43	6	308	1.9	1:51.3	0.86	0.02	0.02	0.02	0.02	0.02	0.0	Burma
WHO South-East Asia Region	2228.78	2710430	775961	56606	1877863	3.0	1:33.2	0.69	0.02	0.02	0.02	0.03	0.03	0.69	WHO South-East Asia Region

A study of the University of Bonn on the spread of Covid-19 at Heinsberg - the most affected county in Germany - showed a rate of deaths to infected of 0.37%. As this is the first reliable data on this ratio I use it as a projection from the number of reported deaths to the spread of the disease in the whole population, given as percentage. Note that locally other factors, like a developing spread, unreported deaths or a situation where people are more prone to die due to an overstretch of the health system will affect this number. Countries with a different population structure (eg. more young vs. old) may also get other ratios, so take this with a grain of salt - I will keep an eye on the developing scientific results.
Links (German):
Preliminary results - Press coverage: Die Welt