COVID-19 - WHO South-East Asia Region - 20-11-27

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	11080558	497.2	56127	0.51%	0.52%
Active cases	693602	31.1	4423	0.64%	0.58%
Deaths	170720	7.7	769	0.45%	0.36%
Recovered	10216236	458.4	50935	0.5%	0.41%

Deaths per infected	1.54%
Recovered per infected	92.2%
Active per infected	6.26%
Deaths per recovered	1.67%
Projection: Total Case Percentage	2.07%

	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	136d 11h	134d 9h
Time to reach a million cases
Time to saturate the population	stable	stable

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:	192	Population	na
	Total cases	Cases per 100.000	Average grow rate (5 days)
Infected	na	95	107
Active	na	102	83
Deaths	na	89	86
Recovered	na	85	92
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	392356	46861	7942	337553	0.81	3.51	0.52	0.3	86d 9h	134d 7h	179.1	21.4	3.6	154.1	2.4	1:42.6	0.86
Indonesia	266.912	522581	68604	16521	437456	0.98	0.98	0.58	0.73	70d 22h	119d 6h	195.8	25.7	6.2	163.9	3.8	1:26.5	0.84
Thailand	66.484	3966	108	60	3798	0.23	3.74	0.0	0.13	296d 21h		6.0	0.2	0.1	5.7	1.6	1:63.3	0.96
India	1360.054	9351109	454940	136200	8759969	0.46	0.54	0.29	0.36	151d 16h	236d 2h	687.6	33.5	10.0	644.1	1.6	1:64.5	0.94
Sri Lanka	21.803	22501	6168	107	16226	2.21	0.34	2.63	2.38	31d 16h	26d 17h	103.2	28.3	0.5	74.4	0.7	1:151.5	0.72
Bangladesh	168.304	458711	78491	6544	373676	0.5	-0.02	0.42	0.49	138d 1h	164d 10h	272.5	46.6	3.9	222.0	1.8	1:57.1	0.81
Maldives	0.375	12933	1138	46	11749	0.51	3.31	0.0	0.2	136d 0h		3450.6	303.6	12.3	3134.7	0.4	1:256.4	0.91
Bhutan	0.742	395	23	0	372	0.67	-0.46	0	0.44	103d 6h		53.3	3.1	0.0	50.2	0.0	na	0.94
Nepal	29.61	229343	18473	1435	209435	0.81	-3.35	1.34	1.03	86d 5h	51d 22h	774.6	62.4	4.8	707.3	0.7	1:144.9	0.91
Burma	68.67	86633	18796	1865	65972	1.8	0.01	1.2	1.94	38d 21h	57d 22h	126.2	27.4	2.7	96.1	2.8	1:35.3	0.76
WHO South-East Asia Region	2228.78	11080558	693602	170720	10216236	0.52	0.58	0.36	0.41	134d 9h	195d 0h	497.2	31.1	7.7	458.4	1.7	1:59.9	0.92

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	392356	46861	7942	337553	2.4	1:42.6	0.86	0.02	0.02	0.02	0.02	0.02	0.98	Pakistan
Indonesia	266.912	522581	68604	16521	437456	3.8	1:26.5	0.84	0.03	0.03	0.03	0.03	0.04	1.67	Indonesia
Thailand	66.484	3966	108	60	3798	1.6	1:63.3	0.96	0.02	0.02	0.02	0.02	0.02	0.02	Thailand
India	1360.054	9351109	454940	136200	8759969	1.6	1:64.5	0.94	0.01	0.01	0.01	0.02	0.02	2.71	India
Sri Lanka	21.803	22501	6168	107	16226	0.7	1:151.5	0.72	0.0	0.01	0.01	0.01	0.01	0.13	Sri Lanka
Bangladesh	168.304	458711	78491	6544	373676	1.8	1:57.1	0.81	0.01	0.01	0.01	0.01	0.02	1.05	Bangladesh
Maldives	0.375	12933	1138	46	11749	0.4	1:256.4	0.91	0.0	0.0	0.0	0.0	0.0	3.32	Maldives
Bhutan	0.742	395	23	0	372	0.0	na	0.94	0.0	0.0	0.0	0.0	0.0	0.0	Bhutan
Nepal	29.61	229343	18473	1435	209435	0.7	1:144.9	0.91	0.01	0.01	0.01	0.01	0.01	1.31	Nepal
Burma	68.67	86633	18796	1865	65972	2.8	1:35.3	0.76	0.02	0.02	0.02	0.03	0.03	0.73	Burma
WHO South-East Asia Region	2228.78	11080558	693602	170720	10216236	1.7	1:59.9	0.92	0.02	0.02	0.02	0.02	0.02	2.07	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