Table 1.

Heat-related, cold-related, and net excess morbidity in diarrhea (%) with 95% empirical Confidence Interval (eCI) by period under four climate change scenarios (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) in Japan. Heat-related and cold-related morbidity were estimated using a two-stage time-series regression model with quasi-Poisson family (Gasparrini et al. 2017). Estimates are presented as GCM-ensemble average decadal fractions.

Scenario	Effect	Period
		2010–2019	2050–2059	2090–2099
RCP2.6	Heat	5.8 (4.4, 6.9)	6.6 (4.9, 8.1)	6.3 (4.7, 7.6)
	Cold	62.6 (57.4, 65.5)	60.7 (54.9, 64.7)	61.2 (56.0, 64.9)
	Net	—	$-1.1$ ($-3.0$, 0.3)	$-0.8$ ($-2.3$, 0.5)
RCP4.5	Heat	5.7 (4.3, 6.8)	7.0 (5.2, 8.3)	7.3 (5.2, 8.9)
	Cold	62.9 (57.7, 65.9)	59.4 (54.1, 63.2)	57.4 (51.7, 61.6)
	Net	—	$-2.1$ ($-3.8$, 0.1)	$-3.8$ ($-6.1$, $-1.7$)
RCP6.0	Heat	5.7 (4.3, 6.8)	6.7 (4.9, 8.0)	8.1 (5.5, 10.2)
	Cold	63.1 (57.9, 66.2)	59.9 (54.5, 63.4)	55.5 (49.5, 60.2)
	Net	—	$-2.2$ ($-3.6$, $-0.6$)	$-5.1$ ($-7.7$, $-2.8$)
RCP8.5	Heat	5.7 (4.4, 6.8)	7.4 (5.3, 9.0)	9.7 (4.9, 12.0)
	Cold	62.5 (57.4, 65.6)	57.5 (51.9, 61.4)	49.5 (42.0, 57.1)
	Net	—	$-3.4$ ($-5.6$, $-1.8$)	$-9.1$ ($-15.5$, $-4.2$)

Note: —, no data; GCM, general circulation model; RCP, representative concentration pathway.