Seasonal Bordetella pertussis pattern in the period from 2008 to 2018 in Germany

Periodic Characteristics of Hepatitis Virus Infections From 2013 to 2020 and Their Association With Meteorological Factors in Guangdong, China: Surveillance Study

BACKGROUND

In the past few decades, liver disease has gradually become one of the major causes of death and illness worldwide. Hepatitis is one of the most common liver diseases in China. There have been intermittent and epidemic outbreaks of hepatitis worldwide, with a tendency toward cyclical recurrences. This periodicity poses challenges to epidemic prevention and control.

OBJECTIVE

In this study, we aimed to investigate the relationship between the periodic characteristics of the hepatitis epidemic and local meteorological elements in Guangdong, China, which is a representative province with the largest population and gross domestic product in China.

METHODS

Time series data sets from January 2013 to December 2020 for 4 notifiable infectious diseases caused by hepatitis viruses (ie, hepatitis A, B, C, and E viruses) and monthly data of meteorological elements (ie, temperature, precipitation, and humidity) were used in this study. Power spectrum analysis was conducted on time series data, and correlation and regression analyses were performed to assess the relationship between the epidemics and meteorological elements.

RESULTS

The 4 hepatitis epidemics showed clear periodic phenomena in the 8-year data set in connection with meteorological elements. Based on the correlation analysis, temperature demonstrated the strongest correlation with hepatitis A, B, and C epidemics, while humidity was most significantly associated with the hepatitis E epidemic. Regression analysis revealed a positive and significant coefficient between temperature and hepatitis A, B, and C epidemics in Guangdong, while humidity had a strong and significant association with the hepatitis E epidemic, and its relationship with temperature was relatively weak.

CONCLUSIONS

These findings provide a better understanding of the mechanisms underlying different hepatitis epidemics and their connection to meteorological factors. This understanding can help guide local governments in predicting and preparing for future epidemics based on weather patterns and potentially aid in the development of effective prevention measures and policies.

Oscillatory properties of class C notifiable infectious diseases in China from 2009 to 2021

Background

Epidemics of infectious diseases have a great negative impact on people's daily life. How it changes over time and what kind of laws it obeys are important questions that researchers are always interested in. Among the characteristics of infectious diseases, the phenomenon of recrudescence is undoubtedly of great concern. Understanding the mechanisms of the outbreak cycle of infectious diseases could be conducive for public health policies to the government.

Method

In this study, we collected time-series data for nine class C notifiable infectious diseases from 2009 to 2021 using public datasets from the National Health Commission of China. Oscillatory power of each infectious disease was captured using the method of the power spectrum analysis.

Results

We found that all the nine class C diseases have strong oscillations, which could be divided into three categories according to their oscillatory frequencies each year. Then, we calculated the oscillation power and the average number of infected cases of all nine diseases in the first 6 years (2009-2015) and the next 6 years (2015-2021) since the update of the surveillance system. The change of oscillation power is positively correlated to the change in the number of infected cases. Moreover, the diseases that break out in summer are more selective than those in winter.

Conclusion

Our results enable us to better understand the oscillation characteristics of class C infectious diseases and provide guidance and suggestions for the government's prevention and control policies.

Changes in temporal properties for epidemics of notifiable infectious diseases in China during the COVID-19 epidemic: population-based surveillance study

BACKGROUND

The COVID-19 was first reported in 2019, and the Chinese government immediately carried out stringent and effective control measures in response to the epidemics.

OBJECTIVE

These non-pharmaceutical interventions may have impacted incidences of other infectious diseases as well. Potential explanations underlying this reduction, however, are not clear. Hence, in this study, we aimed to study the influence of the COVID-19 prevention policies on other infectious diseases (mainly class B infectious diseases) in China.

METHODS

The time-series datasets between 2017 and 2021 for 23 notifiable infectious diseases were extracted from public datasets from the National Health Commission of China. Several indices (peak and trough amplitude, infection selectivity, preferred time to outbreak, oscillatory strength) of each infectious disease were calculated before and after the COVID-19 outbreak.

RESULTS

We found that the prevention and control policies for COVID-19 had a strong significant reduction effect on outbreaks of other infectious diseases. A clear event-related trough (ERT) was observed after the outbreak of COVID-19 under the strict control policies, and its decreasing amplitude is related to the infection selectivity and preferred outbreak time of the disease before the COVID-19. We also calculated the oscillatory strength before and after the COVID-19 outbreak and found that it is significantly stronger before the COVID-19 outbreak, and does not correlate with the trough amplitude.

CONCLUSIONS

Our results directly demonstrate that prevention policies for the COVID-19 have immediate additional benefits for controlling most class B infectious diseases, and several factors (infection selectivity, preferred outbreak time) may have contributed to the reduction of outbreaks. This study may guide the implementation of non-pharmaceutical interventions to control a wider range of infectious diseases.

CLINICALTRIAL

Pertussis surveillance results from a French general practitioner network, France, 2017 to 2020

Introduction

In France, three complementary surveillance networks involving hospitals and paediatrician practices currently allow pertussis surveillance among infants (<1 year old) and children (1–12 years old). Data on incidences among adolescents (13–17 years old) and adults (≥ 18 years) are scarce. In 2017, a sentinel surveillance system called Sentinelles network, was implemented among general practitioners (GPs).

Aim

The purpose of Sentinelles network is to assess pertussis incidence, monitor the cases’ age distribution and evaluate the impact of the country’s vaccination policy. We present the results from the first 4 years of this surveillance.

Methods

GPs of the French Sentinelles network reported weekly numbers of epidemiologically or laboratory-confirmed cases and their characteristics.

Results

A total of 132 cases were reported over 2017–2020. Estimated national incidence rates per 100,000 inhabitants were 17 (95% confidence interval (CI): 12–22) in 2017, 10 (95% CI: 6–14) in 2018, 15 (95% CI: 10–20) in 2019 and three (95% CI: 1–5) in 2020. The incidence rate was significantly lower in 2020 than in 2017–2019. Women were significantly more affected than men (83/132; 63% of women, p = 0.004); 66% (87/132) of cases were aged 15 years or over (median age: 31.5 years; range: 2 months–87 years). Among 37 vaccinated cases with data, 33 had received the recommended number of doses for their age.

Conclusions

These results concur with incidences reported in other European countries, and with studies showing that the incidences of several respiratory diseases decreased in 2020 during the COVID-19 pandemic. The results also suggest a shift of morbidity towards older age groups, and a rapid waning of immunity after vaccination, justifying to continue this surveillance.

The intracellular phase of extracellular respiratory tract bacterial pathogens and its role on pathogen-host interactions during infection

PURPOSE OF REVIEW

An initial intracellular phase of usually extracellular bacterial pathogens displays an important strategy to hide from the host's immune system and antibiotics therapy. It helps the bacteria, including bacterial pathogens of airway diseases, to persist and eventually switch to a typical extracellular infection. Several infectious diseases of the lung are life-threatening and their control is impeded by intracellular persistence of pathogens. Thus, molecular adaptations of the pathogens to this niche but also the host's response and potential targets to interfere are of relevance. Here we discuss examples of historically considered extracellular pathogens of the respiratory airway where the intracellular survival and proliferation is well documented, including infections by Staphylococcus aureus, Bordetella pertussis, Haemophilus influenzae, Pseudomonas aeruginosa, and others.

RECENT FINDINGS

Current studies focus on bacterial factors contributing to adhesion, iron acquisition, and intracellular survival as well as ways to target them for combatting the bacterial infections.

SUMMARY

The investigation of common and specific mechanisms of pathogenesis and persistence of these bacteria in the host may contribute to future investigations and identifications of relevant factors and/or bacterial mechanisms to be blocked to treat or improve prevention strategies.

Enlightenment on oscillatory properties of 23 class B notifiable infectious diseases in the mainland of China from 2004 to 2020

A variety of infectious diseases occur in mainland China every year. Cyclic oscillation is a widespread attribute of most viral human infections. Understanding the outbreak cycle of infectious diseases can be conducive for public health management and disease surveillance. In this study, we collected time-series data for 23 class B notifiable infectious diseases from 2004 to 2020 using public datasets from the National Health Commission of China. Oscillatory properties were explored using power spectrum analysis. We found that the 23 class B diseases from the dataset have obvious oscillatory patterns (seasonal or sporadic), which could be divided into three categories according to their oscillatory power in different frequencies each year. These diseases were found to have different preferred outbreak months and infection selectivity. Diseases that break out in autumn and winter are more selective. Furthermore, we calculated the oscillation power and the average number of infected cases of all 23 diseases in the first eight years (2004 to 2012) and the next eight years (2012 to 2020) since the update of the surveillance system. A strong positive correlation was found between the change of oscillation power and the change in the number of infected cases, which was consistent with the simulation results using a conceptual hybrid model. The establishment of reliable and effective analytical methods contributes to a better understanding of infectious diseases’ oscillation cycle characteristics. Our research has certain guiding significance for the effective prevention and control of class B infectious diseases.