The time needed between an outbreak and consistently weaning porcine reproductive and respiratory (PRRS) virus PCR negative pigs is referred to as time-to-stability (TTS). In this analysis we describe differences in TTS according to the season when the PRRS outbreak occurred in farms located in the Midwestern United States.
161 PRRS outbreaks in 82 sow farms were classified based on the date of the outbreak:
March 21st to June 20th: Spring
June 21st to September 20th: Summer
September 21st to December 20th: Autumn
December 21st to March 20th: Winter
TTS was calculated as the time from the reported PRRS outbreak to the time of the last PRRS PCR negative result in wean-age pigs.
A significant difference was detected in TTS among seasons. The median TTS was higher in spring and summer, compared to autumn and winter.
An explanation for the observed TTS difference among seasons may be found in environmental survivability of the virus as for PRRS outbreaks that occur during spring or summer, the last phase of the stability process coincides with the arrival of winter where the reduced ventilation and decreased temperature within the farm may favor PRRS survival resulting on a lower likelihood of elimination during this time.
This study was conducted using data collected from the Morrison Swine Health Monitoring Project. The main objective of this study was to use time-series analysis to investigate whether yearly patterns commonly described for PRRS were in fact conserved across different U.S. states.
The 268 breeding herds enrolled in this project were the ones that participated in the MSHMP from July 2009 to October 2016. PPRS status of each farm was reported weekly following the AASV guidelines. The five states examined included Minnesota (MN), Iowa (IA), North Carolina (NC), Nebraska (NE), and Illinois (IL).
81 MN farms, 72 IA, 45 NC, 30 NE, 40 from IL, were enrolled in the study with a mean number of animals per site of 2,666; 3,543; 2,342; 4,041; and 4,018 respectively.
The main finding of this study was that PRRS seasonality varies according to geographical region, and the commonly referred “PRRS season” is not necessarily the only time of increase in disease incidence.
Another interesting finding from this study was the presence of an alternating trend for all examined states within of the U.S., except for the state of Iowa, the largest pork producing states in the country (approximately 31.4% of the total US hog and pig inventory), which had an increasing linear trend over the examined years.
In conclusion, PRRS seasonal patterns are not homogeneous across the U.S., with some important pork producing states having biannual PRRS peaks instead of the previously reported winter peak. Findings from this study highlight the importance of coordinating alternative control strategies in different regions considering the prevailing epidemiological patterns, and the need to reinforce strict biosecurity practices beyond the typically described “PRRS season”.
Industry-driven voluntary disease control programs for swine diseases emerged in North America in the early 2000’s, and, since then, those programs have been used for monitoring diseases of economic importance to swine producers. One example of such initiatives is Dr. Morrison’s Swine Health Monitoring Project, a nation-wide monitoring program for swine diseases including the porcine reproductive and respiratory syndrome (PRRS). PRRS has been extensively reported as a seasonal disease in the U.S., with predictable peaks that start in fall and are extended through the winter season. However, formal time series analysis stratified by geographic region has never been conducted for this important disease across the U.S. The main objective of this study was to use approximately seven years of PRRS incidence data in breeding swine herds to conduct time-series analysis in order to describe the temporal patterns of PRRS outbreaks at the farm level for five major swine-producing states across the U.S. including the states of Minnesota, Iowa, North Carolina, Nebraska and Illinois. Data was aggregated retrospectively at the week level for the number of herds containing animals actively shedding PRRS virus. Basic descriptive statistics were conducted followed by autoregressive integrated moving average (ARIMA) modelling, conducted separately for each of the above-mentioned states. Results showed that there was a difference in the nature of PRRS seasonality among states. Of note, when comparing states, the typical seasonal pattern previously described for PRRS could only be detected for farms located in the states of Minnesota, North Carolina and Nebraska. For the other two states, seasonal peaks every six months were detected within a year. In conclusion, we showed that epidemic patterns are not homogeneous across the U.S, with major peaks of disease occurring through the year. These findings highlight the importance of coordinating alternative control strategies in different regions considering the prevailing epidemiological patterns.
Our sixth presentation is by Dr. Andreia Arruda from the Ohio State University sharing the work she did in collaboration with Dr. Morrison regarding PRRS seasonality as well as the environmental factors that are protective against a PRRS outbreak.
The Torremorell lab is continuing to explore swine influenza epidemiology in this recent publication from Dr. Fabian Chamba Pardo in Frontiers in Veterinary Science. After showing that multiple genome constellations of similar and distinct influenza viruses co-circulate in pigs, the group is now presenting new data about influenza herd-level prevalence in the Midwest, and how it is influenced by seasons. Click on the banner below to read the entire research article.
60 sow farms from a single Midwestern production system were enrolled in this study. Between one and seven oral fluid samples were collected at each farm weekly and meteorological data (air temperature and relative humidity) was compiled from stations located from the farms.
28% of submissions had at least one influenza positive result. All farms tested positive at least once during study period. Herd-level prevalence ranged from 7% to 57% as show in the figure above. Prevalence was low in summer, rose during fall, and peaked twice in both early winter (December) and late spring (May). August was the month with the lowest prevalence. Influenza herd-level prevalence was higher when both mean outdoor air temperature and air humidity were lower.
The most common clades identified were H1 delta 1, H1 gamma 1, and clusters H3 IV A and H3 IV B. Furthermore, 21% of the farms had 3 different influenza genetic clades circulating during the study period and 18% had 2.
Influenza is a costly disease for pig producers and understanding its epidemiology is critical to control it. In this study, we aimed to estimate the herd-level prevalence and seasonality of influenza in breed-to-wean pig farms, evaluate the correlation between influenza herd-level prevalence and meteorological conditions, and characterize influenza genetic diversity over time. A cohort of 34 breed-to-wean farms with monthly influenza status obtained over a 5-year period in piglets prior to wean was selected. A farm was considered positive in a given month if at least one oral fluid tested influenza positive by reverse transcriptase polymerase chain reaction. Influenza seasonality was assessed combining autoregressive integrated moving average (ARIMA) models with trigonometric functions as covariates. Meteorological conditions were gathered from local land-based weather stations, monthly aggregated and correlated with influenza herd-level prevalence. Influenza herd-level prevalence had a median of 28% with a range from 7 to 57% and followed a cyclical pattern with levels increasing during fall, peaking in both early winter (December) and late spring (May), and decreasing in summer. Influenza herd-level prevalence was correlated with mean outdoor air absolute humidity (AH) and temperature. Influenza genetic diversity was substantial over time with influenza isolates belonging to 10 distinct clades from which H1 delta 1 and H1 gamma 1 were the most common. Twenty-one percent of farms had three different clades co-circulating over time, 18% of farms had two clades, and 41% of farms had one clade. In summary, our study showed that influenza had a cyclical pattern explained in part by air AH and temperature changes over time, and highlighted the importance of active surveillance to identify high-risk periods when strategic control measures for influenza could be implemented.