COVID-19 - WHO South-East Asia Region - 20-10-09

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	8142098	365.3	82944	1.03%	1.04%
Active cases	1083769	48.6	-8619	-0.79%	-0.59%
Deaths	132400	5.9	1087	0.83%	0.71%
Recovered	6925929	310.7	90476	1.32%	1.07%

Deaths per infected	1.63%
Recovered per infected	85.06%
Active per infected	13.31%
Deaths per recovered	1.91%
Projection: Total Case Percentage	1.61%

	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	67d 16h	67d 5h
Time to reach a million cases
Time to saturate the population	>1yr	>1yr

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	84	65
Active	na	90	134
Deaths	na	81	48
Recovered	na	74	50
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	318266	8646	6558	303062	0.23	-1.74	0.12	0.25	300d 10h	>1yr	145.3	3.9	3.0	138.4	2.2	1:46.3	0.95
Indonesia	266.912	324658	65314	11677	247667	1.36	0.32	0.76	1.33	51d 10h	91d 17h	121.6	24.5	4.4	92.8	4.7	1:21.2	0.76
Thailand	66.484	3634	130	59	3445	0.24	-1.05	0.0	0.3	284d 10h		5.5	0.2	0.1	5.2	1.7	1:58.5	0.95
India	1360.054	6979423	883185	107416	5988822	1.05	-0.89	0.73	1.12	66d 6h	95d 3h	513.2	64.9	7.9	440.3	1.8	1:55.9	0.86
Sri Lanka	21.803	4523	1214	13	3296	6.12	82.06	0.0	0.12	11d 16h		20.7	5.6	0.1	15.1	0.4	1:256.4	0.73
Bangladesh	168.304	375870	80481	5477	289912	0.39	-0.21	0.42	0.47	179d 16h	167d 2h	223.3	47.8	3.3	172.3	1.9	1:52.9	0.77
Maldives	0.375	10808	1120	34	9654	0.52	-0.19	0.0	0.48	132d 23h		2883.7	298.8	9.1	2575.8	0.3	1:285.7	0.89
Bhutan	0.742	306	24	0	282	0.53	-4.02	0	1.49	130d 13h		41.3	3.2	0.0	38.0	0.0	na	0.92
Nepal	29.61	100676	27053	600	73023	3.01	3.85	1.98	2.18	23d 8h	35d 7h	340.0	91.4	2.0	246.6	0.8	1:122.0	0.73
Burma	68.67	23906	16602	566	6738	6.09	5.02	5.41	4.17	11d 17h	13d 3h	34.8	24.2	0.8	9.8	8.4	1:11.9	0.28
WHO South-East Asia Region	2228.78	8142098	1083769	132400	6925929	1.04	-0.59	0.71	1.07	67d 5h	97d 21h	365.3	48.6	5.9	310.7	1.9	1:52.4	0.85

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	318266	8646	6558	303062	2.2	1:46.3	0.95	0.02	0.02	0.02	0.02	0.02	0.81	Pakistan
Indonesia	266.912	324658	65314	11677	247667	4.7	1:21.2	0.76	0.04	0.04	0.04	0.04	0.04	1.18	Indonesia
Thailand	66.484	3634	130	59	3445	1.7	1:58.5	0.95	0.02	0.02	0.02	0.02	0.02	0.02	Thailand
India	1360.054	6979423	883185	107416	5988822	1.8	1:55.9	0.86	0.02	0.02	0.02	0.02	0.02	2.13	India
Sri Lanka	21.803	4523	1214	13	3296	0.4	1:256.4	0.73	0.0	0.0	0.0	0.0	0.0	0.02	Sri Lanka
Bangladesh	168.304	375870	80481	5477	289912	1.9	1:52.9	0.77	0.01	0.01	0.01	0.02	0.02	0.88	Bangladesh
Maldives	0.375	10808	1120	34	9654	0.3	1:285.7	0.89	0.0	0.0	0.0	0.0	0.0	2.45	Maldives
Bhutan	0.742	306	24	0	282	0.0	na	0.92	0.0	0.0	0.0	0.0	0.0	0.0	Bhutan
Nepal	29.61	100676	27053	600	73023	0.8	1:122.0	0.73	0.01	0.01	0.01	0.01	0.01	0.55	Nepal
Burma	68.67	23906	16602	566	6738	8.4	1:11.9	0.28	0.02	0.03	0.03	0.04	0.06	0.22	Burma
WHO South-East Asia Region	2228.78	8142098	1083769	132400	6925929	1.9	1:52.4	0.85	0.02	0.02	0.02	0.02	0.02	1.61	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