Meteorological factors affect the epidemiology of hemorrhagic fever with renal syndrome via altering the breeding and hantavirus-carrying states of rodents and mites: a 9 years’ longitudinal study

Figures & data

Figure 1 Yearly distribution of HFRS in all districts of Qingdao, China, 2007–2015. Hemorrhagic fever with renal syndrome, HFRS.

Table 1 Characteristics of hemorrhagic fever with renal syndrome, Qingdao, China, 2007–2015

Years	Urban districts		Rural-urban fringe zones		Rural counties		Statistical tests
	No. of cases (incidence /10^5)	No. of deaths (mortality /10^5)	No. of cases (incidence/10^5)	No. of deaths (mortality/10^5)	No. of cases (incidence/10^5)	No. of deaths (mortality/10^5)	Incidence^a	Mortality^b
2007	1 (0.06)	0 (0)	7 (0.69)	0 (0)	119 (2.42)	4 (0.08)	χ^2=51.5, P<0.001	P=0.759
2008	2 (0.11)	0 (0)	11 (1.09)	1 (0.10)	214 (4.32)	3 (0.06)	χ^2=94.9, P <0.001	P=0.314
2009	2 (0.11)	0 (0)	9 (0.89)	1 (0.10)	144 (2.91)	5 (0.10)	χ^2=60.0, P <0.001	P=0.459
2010	3 (0.16)	0 (0)	4 (0.40)	0 (0)	174 (3.51)	3 (0.06)	χ^2=83.5, P <0.001	P=0.714
2011	4 (0.19)	0 (0)	10 (0.61)	0 (0)	236 (4.72)	12 (0.24)	χ^2=141.0, P <0.001	P=0.010
2012	6 (0.29)	0 (0)	21 (1.29)	0 (0)	284 (5.60)	3 (0.06)	χ^2=146.8, P <0.001	P=0.763
2013	4 (0.19)	0 (0)	11 (0.67)	0 (0)	221 (4.30)	3 (0.06)	χ^2=124.9, P <0.001	P=0.762
2014	8 (0.38)	0 (0)	9 (0.54)	0 (0)	191 (3.69)	4 (0.08)	χ^2=98.7, P <0.001	P=0.385
2015	4 (0.19)	0 (0)	2 (0.12)	0 (0)	145 (2.78)	2 (0.04)	χ^2=90.3, P <0.001	P=1.000
Total	34 (0.19)	0 (0)	84 (0.69)	2 (0.02)	1728 (3.81)	39 (0.09)	χ^2=872.1, P <0.001	χ^2=21.3, P <0.001

a Chi-square tests was applied to evaluate the difference of HFRS incidence among urban districts, rural-urban fringe zones, and rural countries.

b Fisher exact probability test was applied to evaluate the difference of HFRS mortality among urban districts, rural-urban fringe zones, and rural countries.

Table 2 Association of hantavirus vaccination and the incidence of HFRS in rural counties (Jiaonan, Jiaozhou, Pingdu, Jimo, and Laixi) of Qingdao during 2009–2015

Year	2009	2010	2011	2012	2013	2014	2015
New HFRS cases	144	174	236	284	221	191	145
Accumulative vaccinated population	181 858	316 922	388 584	472 693	473 893	588 449	631 840
Average population	4 940 280	4 952 672	4 996 299	5 072 306	5 135 711	5 177 817	5 208 265
Incidence (/10^5)^a	2.91	3.51	4.72	5.60	4.30	3.69	2.78
Accumulative vaccination rate (%)^a	3.68	6.40	7.78	9.32	9.23	11.36	12.13

a Cochran-Armitage trend test was employed to assess the association of accumulative vaccination rate and the incidence of HFRS, No significant trend was observed (P=0.503).

Figure 2 Monthly incidence of HFRS and meteorological information in Qingdao, 2007–2015. The meteorological information from top to bottom are: (A) temperature (red); (B) relative humidity (blue); (C) rainfall (green); (D) daily sunshine time (brown), respectively. All black lines represent the monthly number of new cases with HFRS.

Table 3 Prevalence of antibodies against hantaviruses in lung tissues of hosts (including rodents and shrews) by species, Qingdao, China, 2011–2015

Species	No. of hosts captured (density, %) /No. of hosts positive for hantavirus (hantavirus-positive rate, %)^a
	2011 (16 707 traps)	2012 (22 654 traps)	2013 (36 166 traps)	2014 (19 611 traps)	2015 (16 016 traps)	Total (111 154 traps)
Apodemus agrarius	9 (0.05)/0 (0)	200 (0.88)/13 (6.50)	303 (0.84)/10 (3.30)	79 (0.49)/4 (5.06)	72 (0.45)/2 (2.78)	663 (0.60)/29 (4.37)
Rattus norvegicus	186 (1.11)/1 (0.54)	391 (1.73)/12 (3.10)	352 (0.97)/19 (5.40)	184 (1.15)/ 4 (2.17)	123 (0.77)/8 (6.50)	1236 (1.11)/44 (3.56)
Mus musculus	123 (0.74)/0 (0)	307 (1.36)/10 (3.26)	432 (1.19)/10 (2.31)	195 (1.22)/5 (2.56)	157 (0.98)/1 (0.64)	1214 (1.09)/26 (2.14)
Rattus rattus	71 (0.42)/0 (0)	4 (0.02)/0 (0)	0 (0)/0 (-)	26 (0.16)/0 (0)	0 (0)/0 (-)	101 (0.09)/0 (0)
Sorex araneus	0 (0)/0 (-)	79 (0.35)/0 (0)	222 (0.61)/0 (0)	33 (0.21)/0 (0)	10 (0.06)/0 (0)	344 (0.31)/0 (0)
Cricetulus triton	0 (0)/0 (-)	141 (0.62)/0 (0)	248 (0.69)/0 (0)	49 (0.31)/0 (0)	16 (0.10)/0 (0)	454 (0.41)/0 (0)
Cricetulus arabensis	4 (0.02)/0 (0)	35 (0.15)/0 (0)	4 (0.01)/0 (0)	3 (0.02)/0 (0)	23 (0.14)/0 (0)	69 (0.06)/0 (0)

a Zero divided by zero cannot be calculated, so the result is replaced by a symbol.

Figure 3 The influences of meteorological factors on the incidence of HFRS in Qingdao, China, 2007–2015. A generalized additive model (GAM) was adopted to fit the HFRS incidence with meteorological factors. Data were divided into two parts. The first 6 years served as training set to build the GAM and the last 3 years were taken as validation set. After selection, temperature, relative humidity and precipitation in the previous quarter were included in the model. Hemorrhagic fever with renal syndrome, HFRS.

Figure 4 The effect values of temperature and relative humidity on the epidemic of HFRS. (A) The effects of temperature with 3 months lag on the incidence of HFRS. (B) The effects of relative humidity with 3 months lag on the incidence of HFRS. The effect value above 0 means a positive effect, while below 0 means a negative effect; degree of freedom, DF; hemorrhagic fever with renal syndrome, HFRS.

Figure 5 Phylogenetic analyses of 46 hantaviruses (L segment) isolated in Qingdao, China. ♦ Black diamond symbol: 39 isolates from hosts (including rodents and shrews); △White triangle symbol: three isolates from mites; ○White circular symbol: four isolates from HFRS patients. hemorrhagic fever with renal syndrome, HFRS.