The influence of climate on influenza A virus (IAV) introductions in Minnesota turkeys: Spring 2007 - 2015

Xi Guo1, Nitipong Homwong2, Jeanette Munoz-Aguayo3, Cristian Flores3, Carol J. Cardona1

1. Department of Veterinary and Biomedical Sciences, College of Veterinary Medicine, University of Minnesota, Saint Paul, MN. 2. Kasetsart University, Kamphaeng Sean,

Nakhon Pathom, Thailand. 3. Mid-Central Research and Outreach Center, Willmar, MN, US.

Introduction • Climate affects the transmission cycle of infectious diseases.

• The landscape that gives rise to the transmission of influenza A virus (IAV) between wild

and domesticated avian species is greatly impacted by the climate.

• The behavior of the wild waterfowl, the natural host of IAV, is also affected by the climate

condition.

• In the spring of 2015, highly pathogenic avian influenza (HPAI) H5N2 was introduced to

turkeys in Minnesota (MN). Prior to 2015, there were seven low pathogenic avian influenza

(LPAI) introductions occurred in the same area and the same season in the turkey flocks.

Objective • To characterize the climate conditions associated with the Spring introductions of IAV in MN

turkeys.

Data analysis • Daily climatic variables including maximum temperature, minimum temperature and snow

depths during 1960-2015 were retrieved from the National Climatic Data Center (NCDC)

archives. The weather stations selected for data analysis were within 20 miles of the case

sites, which were clustered into five regions.

• Weather indicator correlation analysis

• Spearman correlation was performed between the week of the introduction cases and the

weather indicators including temperature 7 to 9°C, heading degree days (HDD) 18 to 20

days, and the yearly average temperature.

• The cumulative days above freezing point during Feb 15 - Mar 15 during 2007 - 2015 were

calculated. Spearman correlation was performed between the cumulative days above the

freezing point and the week of the introductions.

• Snow depth analysis: Wilcoxon Ranked-sum tests were performed to compare the sum of

snow depths between introduction years and non-introduction years.

Results - B. Correlation between the weather indicators and the timing of the introductions

Results - A. The temporal pattern of daily temperatures

Acknowledgement

•We thank

Pomeroy Legacy

Scholarship for

providing the

funding for the

study.

Conclusion and future direction • The similar temporal patterns of Case 8 and the HPAI cases from other

locations suggest a universal climatic condition that drives the occurrence

of HPAI outbreak.

• Several weather indicators correlate with the timing of the introductions.

These indicators could help to predict the timing of the next IAV introduction

in turkey flocks.

Table 3. Correlation analysis between the weather indicators and the weeks of cases (*p

< 0.05)

Figure 2. Daily minimum temperature of first 150 days in the years of all cases (Blue: lowest

temperature point; Purple: yearly average temperature point; Green: date of the case)

Weather indicator Spearman correlation p

value

Spearman correlation coefficient

The  week  when  weekly  average  temperature  was  the  closest  to  7  °C

0.2005 0.5062

The  week  when  weekly  average  temperature  was  the  closest  to  8  °C

0.0083* 0.8447

The  week  when  weekly  average  temperature  was  the  closest  to  9  °C

0.0532 0.7000

The week when weekly average temperature was the closest to the

yearly average

0.1344 0.5768

The week in which weekly average HDD was the closest to 18

0.0083* 0.8447

The week in which weekly average HDD was the closest to 19

0.0137* 0.8149

The week in which weekly average HDD was the closest to 20

0.2005 0.5062

Date

P > 0.05P < 0.05

Case ID Year Date Subtype County

1 2007 03/22* H7N9 Brown

2 2009 05/06* H7N9 Redwood

3 2011 05/13* H7N9 Wright

4 2012 04/26* H8N4 Kandiyohi

5 2013 05/08* H3N2/H9N2 Kandiyohi

6 2014 05/09 H4N2 Kandiyohi7 2015 02/27 H5N2 Pope8 2015 03/22 H5N2 Lac Qui Parle

Table 1. List of the IAV introduction cases in

Minnesota, 2007 - 2015

Figure 1. Map of the IAV introduction

cases by counties, 2007 - 2015 • Case 7 happened 4 days after the lowest temperature point.

• The relationship between Case 7 and the lowest point resembles the temporal pattern illustrated

by Liu et al (Plos one, 2007), recapitulating the same climate condition for HPAI introductions.

• The Ukraine case locate in the same level of latitude with the Case 7.

• The temperature pattern of other LPAI cases is different from Case 7, suggesting different

mechanism of HPAI and LPAI introductions.

Jan 1 - May 29

Tem

pera

ture

(°C

)

Case ID

Selected HPAI H5N1 virus outbreaks and the minimum temperatures and dates at nearby WMO (World Meteorological Organization)

stations. (Liu et al, Temperature Drops and the Onset of Severe Avian Influenza A H5N1 Virus Outbreaks. Plos One, 2007)

Variation of daily minimum

temperatures at WMO stations near

H5N1 Virus outbreak areas (Liu, et

al; Plos one, 2007)

• Several weather indicators have

significant positive correlations with

the timing of introductions (p <

0.05).

Figure 3. P Value of spearman correlation test from the count of the

accumulative days above freezing point (X-axis is the date to count the

accumulative days in each cases; Y-axis is p-value. Red point: P-value >

0.05. Green point: P-value < 0.05.)

• The cumulative days

during Feb 22 - Mar 5

were associated with

the week of the cases

(P < 0.05).

Results - C. Snow depths analysisCase Rank  (From  low  to  high) Wilcoxon  P  value

1 26  out  of  56 0.90

2 21  out  of  56 0.66

3 40  out  of  56 0.50

4 27  out  of  54 1.00

5 54  out  of  56 0.12

6 49  out  of  56 0.21

7 11  out  of  56 0.29

8 4  out  of  55 0.14

Table 4. Wilcoxon signed rank test on the yearly

sum of the snow depths prior to the introduction

dates

• Case 7 and 8 have lower snow

depths than non-introduction

years. Other cases have average

level of snow depths among all

the year.

Snow depths (normalized)

Temperature (normalized)