{"id":8405,"date":"2020-05-01T11:58:35","date_gmt":"2020-05-01T15:58:35","guid":{"rendered":"https:\/\/demand-planning.com\/?p=8405"},"modified":"2020-05-05T12:59:44","modified_gmt":"2020-05-05T16:59:44","slug":"coronavirus-forecasts-2","status":"publish","type":"post","link":"https:\/\/demand-planning.com\/2020\/05\/01\/coronavirus-forecasts-2\/","title":{"rendered":"COVID-19 USA & NEW YORK ROLLING FORECASTS"},"content":{"rendered":"

The following is a daily rolling forecast of Covid-19 cases and deaths in the USA and New York State, looking 2 months ahead. It is prepared by Dr. Chaman L. Jain, Professor of Economics at St. John’s University, and author of the book, <\/b>Fundamentals of Demand Planning & Forecasting<\/a>. <\/em>This forecast <\/strong>will be updated weekly as new data emerges.\u00a0<\/b><\/p>\n

When preparing a forecast for something new, whether it\u2019s a product or a virus, we typically identify an analogous \u201citem\u201d. We identify how the analogous item behaved in the past to predict how the new item will behave in the future. But the patterns of Covid-19 cases and deaths do not correspond with any virus we have experienced before, making this impossible. Further, the patterns in countries like South Korea and China that have nearly gone through the whole coronavirus cycle, do not match with what we are currently experiencing in the U.S.A. Therefore, the only option we have is to study the pattern of cases in the U.S.A. and then extrapolate it going forward. We now have enough data to do so.<\/p>\n

Forecasting Coronavirus Cases & Mortality In The United States<\/strong><\/h2>\n

Usually, the pattern of a virus (like a new product in business) forms a S curve where it first increases at an accelerated rate and then increases at a decelerating rate. This is exactly what we are seeing in the U.S.A. Covid-19 data. Data shows that we reached the point of inflection in the week of March 16th<\/sup>, a key turning point when the daily percentage increase in total cases started increasing but at a decreasing rate. In that week, the weekly average of daily increases as a percentage of total cases hit 38%. Thereafter, it started declining and fell to 3.6% in the week of April 20th. I believe this pattern will continue and that the total number of cases in the U.S.A. will hit 1.7 million by June 30th<\/sup>. After that, we will still have cases of coronavirus, though their number will be much smaller.<\/p>\n

The U.S death rate from coronavirus also follows a similar pattern. It reached its point of inflection in the week of April 20th<\/sup> when the weekly average of daily deaths as a percentage of total cases reached 0.2%. I expect this percentage will continue to slowly decline. With that, I expect the death toll in the U.S to reach 170,000 by June 30th<\/sup>.<\/p>\n

New York State Forecasts<\/strong><\/h2>\n

Among all the states, New York state has been hit the hardest. In this state, the pattern of people affected by the virus is very similar to that of the \u00a0U.S.A. as a whole. The weekly average of daily percentage increases in total cases peaked in the week of March 16th <\/sup>when it rose to 58%. Thereafter, it started declining and reached 2.5% in the week of April 20th<\/sup>. I expect this pattern to continue and that the number of cases in New York will reach 385,000 by June 30th<\/sup>.<\/p>\n

Regarding the number of deaths in New York state, the pattern is the same as the total number of cases. The daily number of deaths as a percentage of total cases kept on rising until the week of March 30th<\/sup>. Thereafter it declined and is expected to decline further. With that, the total number of deaths in New York State is predicted to reach 30,000 by June 30th.<\/p>\n

It should be noted that every forecast is based on certain assumptions. A key assumption here is that things will continue the way they have in the past. During the time period observed to create our forecasts, no vaccine to treat this virus was available. The development of such a vaccine would cause us to revisit our forecasts.<\/p>\n

\u00a0<\/strong>Daily forecasts are provided in Table 1. One can observe how accurate they are by comparing each day\u2019s forecasts with actuals.<\/p>\n\n\n\n\n\n\n
\n

Forecasts Of Coronavirus Cases & Deaths<\/strong><\/h3>\n<\/td>\n<\/tr>\n

<\/td>\nUSA<\/strong><\/td>\nNEW YORK STATE<\/strong><\/td>\n<\/tr>\n
Date<\/strong><\/td>\nAccumulated Total Cases<\/strong><\/td>\nAccumulated<\/strong><\/p>\n

Total Deaths<\/strong><\/td>\n

Accumulated Total Cases<\/strong><\/td>\nAccumulated<\/strong><\/p>\n

Total Deaths<\/strong><\/td>\n<\/tr>\n

30-Apr<\/p>\n

1-May<\/p>\n

2-May<\/p>\n

3-May<\/p>\n

4-May<\/p>\n

5-May<\/p>\n

6-May<\/p>\n

7-May<\/p>\n

8-May<\/p>\n

9-May<\/p>\n

10-May<\/p>\n

11-May<\/p>\n

12-May<\/p>\n

13-May<\/p>\n

14-May<\/p>\n

15-May<\/p>\n

16-May<\/p>\n

17-May<\/p>\n

18-May<\/p>\n

19-May<\/p>\n

20-May<\/p>\n

21-May<\/p>\n

22-May<\/p>\n

23-May<\/p>\n

24-May<\/p>\n

25-May<\/p>\n

26-May<\/p>\n

27-May<\/p>\n

28-May<\/p>\n

29-May<\/p>\n

30-May<\/p>\n

31-May<\/p>\n

1-Jun<\/p>\n

2-Jun<\/p>\n

3-Jun<\/p>\n

4-Jun<\/p>\n

5-Jun<\/p>\n

6-Jun<\/p>\n

7-Jun<\/p>\n

8-Jun<\/p>\n

9-Jun<\/p>\n

10-Jun<\/p>\n

11-Jun<\/p>\n

12-Jun<\/p>\n

13-Jun<\/p>\n

14-Jun<\/p>\n

15-Jun<\/p>\n

16-Jun<\/p>\n

17-Jun<\/p>\n

18-Jun<\/p>\n

19-Jun<\/p>\n

20-Jun<\/p>\n

21-Jun<\/p>\n

22-Jun<\/p>\n

23-Jun<\/p>\n

24-Jun<\/p>\n

25-Jun<\/p>\n

26-Jun<\/p>\n

27-Jun<\/p>\n

28-Jun<\/p>\n

29-Jun<\/p>\n

30-Jun<\/td>\n

1,088,033<\/p>\n

1,112,407<\/p>\n

1,137,326<\/p>\n

1,162,803<\/p>\n

1,183,949<\/p>\n

1,205,479<\/p>\n

1,227,401<\/p>\n

1,249,721<\/p>\n

1,272,448<\/p>\n

1,295,587<\/p>\n

1,319,148<\/p>\n

1,335,319<\/p>\n

1,351,689<\/p>\n

1,368,259<\/p>\n

1,385,033<\/p>\n

1,402,012<\/p>\n

1,419,200<\/p>\n

1,436,598<\/p>\n

1,448,470<\/p>\n

1,460,440<\/p>\n

1,472,510<\/p>\n

1,484,679<\/p>\n

1,496,949<\/p>\n

1,509,320<\/p>\n

1,521,793<\/p>\n

1,530,271<\/p>\n

1,538,796<\/p>\n

1,547,369<\/p>\n

1,555,990<\/p>\n

1,564,658<\/p>\n

1,573,375<\/p>\n

1,582,141<\/p>\n

1,588,083<\/p>\n

1,594,047<\/p>\n

1,600,034<\/p>\n

1,606,043<\/p>\n

1,612,075<\/p>\n

1,618,129<\/p>\n

1,624,206<\/p>\n

1,628,318<\/p>\n

1,632,441<\/p>\n

1,636,574<\/p>\n

1,640,717<\/p>\n

1,644,871<\/p>\n

1,649,036<\/p>\n

1,653,211<\/p>\n

1,656,032<\/p>\n

1,658,859<\/p>\n

1,661,690<\/p>\n

1,664,526<\/p>\n

1,667,367<\/p>\n

1,670,213<\/p>\n

1,673,064<\/p>\n

1,674,989<\/p>\n

1,676,916<\/p>\n

1,678,845<\/p>\n

1,680,777<\/p>\n

1,682,711<\/p>\n

1,684,647<\/p>\n

1,686,585<\/p>\n

1,687,893<\/p>\n

1,689,202<\/strong><\/td>\n

63,896<\/p>\n

66,187<\/p>\n

68,529<\/p>\n

70,923<\/p>\n

73,049<\/p>\n

75,213<\/p>\n

77,417<\/p>\n

79,661<\/p>\n

81,946<\/p>\n

84,273<\/p>\n

86,641<\/p>\n

88,733<\/p>\n

90,849<\/p>\n

92,992<\/p>\n

95,161<\/p>\n

97,356<\/p>\n

99,579<\/p>\n

101,828<\/p>\n

103,807<\/p>\n

105,801<\/p>\n

107,812<\/p>\n

109,840<\/p>\n

111,884<\/p>\n

113,945<\/p>\n

115,758<\/p>\n

117,580<\/p>\n

119,413<\/p>\n

121,256<\/p>\n

123,109<\/p>\n

124,972<\/p>\n

126,846<\/p>\n

128,731<\/p>\n

130,380<\/p>\n

132,036<\/p>\n

133,698<\/p>\n

135,366<\/p>\n

137,040<\/p>\n

138,721<\/p>\n

140,408<\/p>\n

141,883<\/p>\n

143,361<\/p>\n

144,844<\/p>\n

146,330<\/p>\n

147,820<\/p>\n

149,313<\/p>\n

150,811<\/p>\n

152,119<\/p>\n

153,429<\/p>\n

154,742<\/p>\n

156,057<\/p>\n

157,374<\/p>\n

158,693<\/p>\n

160,015<\/p>\n

161,169<\/p>\n

162,324<\/p>\n

163,481<\/p>\n

164,639<\/p>\n

165,798<\/p>\n

166,958<\/p>\n

168,120<\/p>\n

169,134<\/p>\n

170,149<\/strong><\/td>\n

303,917<\/p>\n

308,203<\/p>\n

312,549<\/p>\n

316,957<\/p>\n

319,970<\/p>\n

323,011<\/p>\n

326,082<\/p>\n

329,182<\/p>\n

332,311<\/p>\n

335,470<\/p>\n

338,659<\/p>\n

340,830<\/p>\n

343,014<\/p>\n

345,212<\/p>\n

347,425<\/p>\n

349,651<\/p>\n

351,892<\/p>\n

354,147<\/p>\n

355,677<\/p>\n

357,213<\/p>\n

358,757<\/p>\n

360,307<\/p>\n

361,863<\/p>\n

363,426<\/p>\n

364,996<\/p>\n

366,059<\/p>\n

367,126<\/p>\n

368,195<\/p>\n

369,267<\/p>\n

370,342<\/p>\n

371,421<\/p>\n

372,503<\/p>\n

373,234<\/p>\n

373,967<\/p>\n

374,701<\/p>\n

375,437<\/p>\n

376,174<\/p>\n

376,912<\/p>\n

377,652<\/p>\n

378,152<\/p>\n

378,653<\/p>\n

379,154<\/p>\n

379,656<\/p>\n

380,158<\/p>\n

380,661<\/p>\n

381,165<\/p>\n

381,505<\/p>\n

381,845<\/p>\n

382,186<\/p>\n

382,527<\/p>\n

382,868<\/p>\n

383,210<\/p>\n

383,552<\/p>\n

383,783<\/p>\n

384,014<\/p>\n

384,244<\/p>\n

384,476<\/p>\n

384,707<\/p>\n

384,938<\/p>\n

385,170<\/p>\n

385,326<\/p>\n

385,482<\/strong><\/td>\n

18,015<\/p>\n

18,349<\/p>\n

18,687<\/p>\n

19,031<\/p>\n

19,325<\/p>\n

19,622<\/p>\n

19,923<\/p>\n

20,226<\/p>\n

20,532<\/p>\n

20,840<\/p>\n

21,152<\/p>\n

21,419<\/p>\n

21,687<\/p>\n

21,957<\/p>\n

22,229<\/p>\n

22,503<\/p>\n

22,778<\/p>\n

23,055<\/p>\n

23,292<\/p>\n

23,529<\/p>\n

23,768<\/p>\n

24,008<\/p>\n

24,248<\/p>\n

24,490<\/p>\n

24,733<\/p>\n

24,940<\/p>\n

25,147<\/p>\n

25,355<\/p>\n

25,564<\/p>\n

25,773<\/p>\n

25,983<\/p>\n

26,194<\/p>\n

26,373<\/p>\n

26,553<\/p>\n

26,733<\/p>\n

26,914<\/p>\n

27,094<\/p>\n

27,275<\/p>\n

27,457<\/p>\n

27,611<\/p>\n

27,766<\/p>\n

27,921<\/p>\n

28,076<\/p>\n

28,231<\/p>\n

28,387<\/p>\n

28,542<\/p>\n

28,675<\/p>\n

28,807<\/p>\n

28,940<\/p>\n

29,073<\/p>\n

29,206<\/p>\n

29,339<\/p>\n

29,472<\/p>\n

29,585<\/p>\n

29,699<\/p>\n

29,812<\/p>\n

29,925<\/p>\n

30,039<\/p>\n

30,153<\/p>\n

30,266<\/p>\n

30,380<\/p>\n

30,477<\/strong><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u00a0Check back next week for the updated forecast.<\/strong><\/p>\n<\/span>","protected":false},"excerpt":{"rendered":"

The following is a daily rolling forecast of Covid-19 cases and deaths in the USA and New York State, looking 2 months ahead. It is prepared by Dr. Chaman L. Jain, Professor of Economics at St. John’s University, and author of the book, Fundamentals of Demand Planning & Forecasting. This forecast will be updated weekly […]<\/p>\n","protected":false},"author":4,"featured_media":8411,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[386],"tags":[511,505,512],"class_list":{"0":"post-8405","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-analytics","8":"tag-black-swan","9":"tag-coronavirus","10":"tag-covid-19"},"_links":{"self":[{"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/posts\/8405"}],"collection":[{"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/comments?post=8405"}],"version-history":[{"count":0,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/posts\/8405\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/media\/8411"}],"wp:attachment":[{"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/media?parent=8405"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/categories?post=8405"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/demand-planning.com\/wp-json\/wp\/v2\/tags?post=8405"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}