Association of weather variability with resurging pertussis infections among different age groups: A non-linear approach

Modelling of potential risk areas of pertussis cases in the Philippines using bioclimatic envelopes

OBJECTIVES

Pertussis remains a pressing public health concern in the Philippines despite being vaccine-preventable. The resurgence of the disease, driven by waning immunity, vaccine hesitancy and erratic outbreaks, underscores the need for innovative surveillance methods. Thus, this study intends to create a predictive model of potential risk areas for pertussis outbreaks in the Philippines using bioclimatic variables.

METHODS

This study employs the maximum entropy algorithm to predict pertussis risk areas in the Philippines based on 19 bioclimatic variables. The occurrence data of reported pertussis cases were obtained from two sources: the National Disaster Risk Reduction and Management Council, covering 30 March-11 June 2024, and the Weekly Epidemiological Surveillance Report, spanning 1 January-12 October 2024.

RESULTS

Key variables such as Mean Temperature of the Wettest Quarter (BIO8), Precipitation of the Wettest Quarter (BIO16) and Precipitation of the Driest Quarter (BIO17) were identified as significant predictors. Results revealed high-risk areas concentrated in northern Luzon, particularly Central Luzon (Region III), the major coastal areas of Ilocos (Region I), National Capital Region, MIMAROPA (Region IV-B), and an isolated area in Bicol (Region V). The model performance indicates excellent predictive accuracy (AUC = 0.972).

CONCLUSION

The findings highlight how climatic factors shape pertussis distribution through anthropogenic means (e.g., higher humidity increases the chances of acquiring respiratory problems), providing a framework for eco-epidemiological risk assessment. This approach enhances targeted intervention planning, resource allocation, and early warning systems, particularly in resource-limited settings like the Philippines. The study underscores the role of Maximum Entropy in addressing re-emerging diseases, contributing to sustainable public health preparedness and mitigation strategies in tropical regions given that there is currently no predictive model for pertussis cases in the Philippines.

Impact of outdoor air pollution on the incidence of pertussis in China: a time-series study

BACKGROUND

The increasing number of pertussis cases worldwide over the past two decades has challenged healthcare workers, and the role of environmental factors and climate change cannot be ignored. The incidence of pertussis has increased dramatically in mainland China since 2015, developing into a serious public health problem. The association of meteorological factors on pertussis has attracted attention, but few studies have examined the impact of air pollutants on this respiratory disease.

METHODS

In this study, we analyzed the relationship between outdoor air pollution and the pertussis incidence. The study period was from January 2013 to December 2018, and monthly air pollutant data and the monthly incidence of patients in 31 provinces of China were collected. Distributed lag nonlinear model (DLNM) analysis was used to estimate the associations between six air pollutants and monthly pertussis incidence in China.

RESULTS

We found a correlation between elevated pertussis incidence and short-term high monthly CO2 and O3 exposure, with a 10 μg/m3 increase in NO2 and O3 being significantly associated with increased pertussis incidence, with RR values of 1.78 (95% CI: 1.29-2.46) and 1.51 (95% CI: 1.16-1.97) at a lag of 0 months, respectively. Moreover, PM2.5 and SO2 also played key roles in the risk of pertussis surged. These associations remain significant after adjusting for long-term trend, seasonality and collinearity.

CONCLUSIONS

Overall, these data reinforce the evidence of a link between incidence and climate identified in regional and local studies. These findings also further support the hypothesis that air pollution is responsible for the global resurgence of pertussis. Based on this we suggest that public health workers should be encouraged to consider the risks of the environment when focusing on pertussis prevention and control.

The long-term effects of meteorological parameters on pertussis infections in Chongqing, China, 2004-2018

Evidence on the long-term influence of climatic variables on pertussis is limited. This study aims to explore the long-term quantitative relationship between weather variability and pertussis. Data on the monthly number of pertussis cases and weather parameters in Chongqing in the period of 2004-2018 were collected. Then, we used a negative binomial multivariable regression model and cointegration testing to examine the association of variations in monthly meteorological parameters and pertussis. Descriptive statistics exhibited that the pertussis incidence rose from 0.251 per 100,000 people in 2004 to 3.661 per 100,000 persons in 2018, and pertussis was a seasonal illness, peaked in spring and summer. The results from the regression model that allowed for the long-term trends, seasonality, autoregression, and delayed effects after correcting for overdispersion showed that a 1 hPa increment in the delayed one-month air pressure contributed to a 3.559% (95% CI 0.746-6.293%) reduction in the monthly number of pertussis cases; a 10 mm increment in the monthly aggregate precipitation, a 1 °C increment in the monthly average temperature, and a 1 m/s increment in the monthly average wind velocity resulted in 3.641% (95% CI 0.960-6.330%), 19.496% (95% CI 2.368-39.490%), and 3.812 (95% CI 1.243-11.690)-fold increases in the monthly number of pertussis cases, respectively. The roles of the mentioned weather parameters in the transmission of pertussis were also evidenced by a sensitivity analysis. The cointegration testing suggested a significant value among variables. Climatic factors, particularly monthly temperature, precipitation, air pressure, and wind velocity, play a role in the transmission of pertussis. This finding will be of great help in understanding the epidemic trends of pertussis in the future, and weather variability should be taken into account in the prevention and control of pertussis.

Urban Water Consumption Patterns in an Adult Population in Wuxi, China: A Regression Tree Analysis

Understanding water intake variation is crucial for assessing human exposure to water pollutants. The correlation between water intake and demographic factors warrants further exploration. A cross-sectional study was conducted to estimate urban water consumption and its associated factors among adults in Wuxi, China, in 2015. The water consumption information was obtained by a 24-h self-report diary over seven consecutive days. A classification and regression tree (CART) analysis was applied to detect how water consumption varied with the demographic variables. Finally, a total of 1188 adults (18–87 years old) were included. The results demonstrated that the median water consumption of the adults was 1525 mL/day in summer and 1217 mL/day in winter. The results of the CART analysis demonstrated that body mass index (BMI) and age were the leading factors that were associated with water consumption in summer and winter, respectively. The water consumption threshold of BMI for men differed from women (23 kg/m² vs. 18 kg/m²) in summer, and the threshold of age for men was also different from women (43 years vs. 21 years) in winter. In conclusion, the findings are useful for accurately assessing human exposure to water pollutants and identifying the high-risk subgroups.