Ballpark first forecast based on simple math
Avg # tests per day for the last 8 days = 150,025 . . .
(fun fact: during that period on 4 out of 7 days fewer people were tested than on the previous day)
Avg # of new tests are positive in the last 7 days = 28,197
(fun fact: the days with the lowest % of positive cases were the days when the # of tests increased the most = test more people and the % positive falls)
Because the variation in the # of new tests is so great on a day to day basis, and there's no clear trajectory of increasing or decreasing rates of testing, I'm going to use the avg # of tests per day.
Because the % of new cases seems to be linked more closely to the # of tests than to the date, I"m going to use the avg % of new cases.
Therefore: I going to start off assuming that 150,025 x 7 = 1,050,175 new tests will be done by 4/26
and that 18.6% of those tests will be positive , so 1,050,175 x .186 = 195,332 new positive cases
195,332 + 749,203 (current count) = 944,535 positive cases by EoD 4/26
using the average of 28,197 new positive cases per day in the last 7 days = 197,379
197,379 + 749,203 = 946,582 positive cases by EoD 4/26
What might impact the rate of positive cases:
Decrease due to social distancing
Increase due to delay between exposure & symptoms
"France . . . went into lockdown on the 17th March 2020. . . . The lockdown reduced the reproductive number from 3.3 to 0.5 (84% reduction).. . . "
I'm assuming that the lockdown in the US will have/is having a similar effect.