The prediction of pertussis infections cases is widespread domestically and internationally, from seasonal autoregressive integrated moving average (SARIMA) models to nonlinear autoregressive network (NAR) have used time series analysis, and have achieved good results[17]. In the European Centre for Disease Control and Prevention (ECDC), the MEM method is a standardized method for epidemiological classification and early warning of infectious diseases[18]. This study provides an excellent methodology for the exploration of epidemiological trends in pertussis disease, and is considerably more precise and convincing than previous descriptive analyses[19].
Several studies have examined whether individual meteorological and air pollution exposures are associated with pertussis[20]. However, few studies have quantitatively analyzed pertussis and environmental factors. The present study found a positive effect of temperature and SO2 on incidence. Higher temperatures increased the sensitivity of the pertussis vaccine, causing it to change in some way. Also, being in the summer months of an epidemic, high temperatures increase children's access to and exposure to environmental contaminants, keeping the disease and its spread at epidemic levels[21]. This result is similar to a survey showing that both tuberculosis and pertussis were strongly associated with total soot emissions and total SO2 emissions[22]. In recent years, haze pollution has attracted much attention due to its significant impact on public health[23]. In contrast, air pressure, humidity and CO have a negative effect on morbidity. Previous studies have found that the higher the humidity, the faster the growth of B. pertussis on agar plates. In addition, humid environments increase the number of pathogens deposited on the surface of objects, thus increasing the chance of infection[24, 25]. The opposite result may be because the study is in the Shandong Peninsula of China, where the climate is more humid than inland areas at the same latitude, so residents were reluctant to go out in the summer months, and children were exposed to poor indoor air circulation in a room with low relative humidity, which increased their chances of getting sick. The low outdoor concentrations of CO were also due to the lower use of coal during the summer months, which also somewhat caused children to ignore outdoor pollution, allowing for increased exposure to bacteria outdoors.
This study is two-tiered and stratified in its environmental modelling strategy. As we pursued single and mixed pollution analyses and compared similarities and differences in single and mixed meteorological and pollution effects across gender and different onset lag conditions. We found little difference between males and females, but males showed significant significance in the negative CO effect, probably because boys favored outdoor activities and were more likely to have increased exposure to disease pathogens for low levels of CO[26]. In contrast, the positive effect of PM2.5 was significantly significant in the delay 0–10 days, which was similar to the results of a Chinese survey[22]. Within these circumstances, we also explored the overall and interactive effects of pollutants on whooping cough incidence in Jining City, Shandong Province, China, at different prevalence thresholds. The main positive effectors affecting the onset of disease at low and high threshold levels were O3 and SO2, respectively, while the negative effectors were SO2 and CO, respectively. This will provide us with a basis for future monitoring of different contaminants in response to epidemics of pertussis disease, depending on the period of epidemic level.
Although the associations of pertussis with pollutants and meteorological factors were analyzed in depth in this study, the findings could not be extrapolated to all regions of China due to regional limitations. Moreover, because of the large lag between the onset and diagnosis of pertussis in this study, the lagged stratified analysis of environmental factors such as pollutants still leads to uncertainty in the effects of environmental factors, thus paving the way for future researchers to explore their associations.