Seasonal patterns in time series of pertussis

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.

Machine learning clinical decision support systems for surveillance: a case study on pertussis and RSV in children

We tested the performance of a machine learning (ML) algorithm based on signs and symptoms for the diagnosis of RSV infection or pertussis in the first year of age to support clinical decisions and provide timely data for public health surveillance. We used data from a retrospective case series of children in the first year of life investigated for acute respiratory infections in the emergency room from 2015 to 2020. We collected data from PCR laboratory tests for confirming pertussis or RSV infection, clinical symptoms, and routine blood testing results, which were used for the algorithm development. We used a LightGBM model to develop 2 sets of models for predicting pertussis and RSV infection: for each type of infection, we developed one model trained with the combination of clinical symptoms and results from routine blood test (white blood cell count, lymphocyte fraction and C-reactive protein), and one with symptoms only. All analyses were performed using Python 3.7.4 with Shapley values (Shap values) visualization package for predictor visualization. The performance of the models was assessed through confusion matrices. The models were developed on a dataset of 599 children. The recall for the pertussis model combining symptoms and routine laboratory tests was 0.72, and 0.74 with clinical symptoms only. For RSV infection, recall was 0.68 with clinical symptoms and laboratory tests and 0.71 with clinical symptoms only. The F1 score for the pertussis model was 0.72 in both models, and, for RSV infection, it was 0.69 and 0.75. ML models can support the diagnosis and surveillance of infectious diseases such as pertussis or RSV infection in children based on common symptoms and laboratory tests. ML-based clinical decision support systems may be developed in the future in large networks to create accurate tools for clinical support and public health surveillance.

Epidemiological characteristics and seasonal variation of measles, pertussis, and influenza in Kazakhstan between 2010-2020 years

<b>Background: </b>Vaccine-preventable diseases such as pertussis, measles, and influenza remain among the most significant medical and socioeconomic issues in Kazakhstan, despite significant vaccination achievements. Thus, here we aimed to analyze the long-term dynamics and provide information on the current epidemiology of pertussis, measles, and influenza in Kazakhstan.<br /> <b>Methods: </b>A retrospective analysis of the long-term dynamics of infectious diseases was carried out using the data from the statistical collections for 2010-2020 and the Unified Payment System from 2014 to 2020.<br /> <b>Results: </b>During the 2010-2020 years, the long-term dynamics show an unequal distribution of pertussis, measles, and influenza-related morbidity. In comparison with earlier years, registration of infectious disease was the highest in 2019 and 2020. The incidence cases among registered infectious diseases in 2019 were: pertussis-147, measles-13,326, and in 2020: influenza-2,678. High incidence rates have been documented in Pavlodar, North Kazakhstan, Mangystau regions, and the cities of Shymkent and Nur-Sultan. The incidence varies depending on the seasonality: pertussis (summer-autumn), measles (winter-spring), and influenza (mostly in winter).<br /> <b>Conclusion: </b>The findings highlight the importance of focusing more on the characteristics of the epidemic process of vaccine-preventable diseases in order to assess the effectiveness of implemented measures and verify new routes in strengthening the epidemiological surveillance system.

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.

ARIMA and ARIMA-ERNN models for prediction of pertussis incidence in mainland China from 2004 to 2021

OBJECTIVE

To compare an autoregressive integrated moving average (ARIMA) model with a model that combines ARIMA with the Elman recurrent neural network (ARIMA-ERNN) in predicting the incidence of pertussis in mainland China.

BACKGROUND

The incidence of pertussis has increased rapidly in mainland China since 2016, making the disease an increasing public health threat. There is a pressing need for models capable of accurately predicting the incidence of pertussis in order to guide prevention and control measures. We developed and compared two models for predicting pertussis incidence in mainland China.

METHODS

Data on the incidence of pertussis in mainland China from 2004 to 2019 were obtained from the official website of the Chinese Center for Disease Control and Prevention. An ARIMA model was established using SAS (ver. 9.4) software and an ARIMA-ERNN model was established using MATLAB (ver. R2019a) software. The performances of these models were compared.

RESULTS

From 2004 to 2019, there were 104,837 reported cases of pertussis in mainland China, with an increasing incidence over time. The incidence of pertussis showed obvious seasonal characteristics, with the peak lasting from March to September every year. Compared with the mean squared error (MSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) of the ARIMA model, those of the ARIMA-ERNN model were 81.43%, 95.97% and 80.86% lower, respectively, in fitting performance. In terms of prediction performance, the MAE, MSE and MAPE were 37.75%, 56.88% and 43.75% lower, respectively.

CONCLUSION

The fitting and prediction performances of the ARIMA-ERNN model were better than those of the ARIMA model. This provides theoretical support for the prediction of infectious diseases and should be beneficial to public health decision making.

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

IntroductionIn 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).AimThe 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.MethodsGPs of the French Sentinelles network reported weekly numbers of epidemiologically or laboratory-confirmed cases and their characteristics.ResultsA 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.ConclusionsThese 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.

Epidemiology incidence and geographical distribution of Pertussis using GIS and its incidence prediction in Iran in 2021

Background: Pertussis is a respiratory tract infection caused by Bordetella pertussis, which causes inflammation of the lungs and respiratory tract. The purpose of this study was to investigate the incidence and geographical distribution of pertussis using the geographic information system (GIS) and to predict its incidence in Iran in 2021.

Methods: This was a descriptive analytical study. Information on pertussis was obtained from the Center for Communicable Diseases Control during 2009-2015. In the next step, the ArcGIS 9.3 was used to prepare geographic maps of the disease incidence and frequency. Therefore, the disease prediction map was drawn. using the Raster Calculator tool.

Results: The results showed that the highest incidence of pertussis during 2009-2015 was in Zanjan, Qom, Mazandaran, and Qazvin provinces. The incidence of pertussis in Iran increased from 0.74 in 2009 to 1.53 in 2015. Based on the modeling results for Iran, Qom, Mazandaran, Tehran, Qazvin, and Zanjan provinces, with 76.76%, 73.69%, 66.32%, 30.94% and 24.18% of their areas (Km2), are at high risk for pertussis in the coming years, respectively.

Conclusion: The incidence of the disease has been increasing in recent years, indicating the emergence of the disease in Iran. The modeling maps show that the Iranian provinces of Qom, Tehran, Zanjan, and Qazvin are at risk of the disease incidence in the coming years, indicating the need for planning, appropriate interventions and more precise implementation of the vaccination program against the disease.

Forecasting the future number of pertussis cases using data from Google Trends

Background

Alternative methods could be used to enhance the monitoring and forecasting of re-emerging conditions such as pertussis. Here, whether data on the volume of Internet searching on pertussis could complement traditional modeling based solely on reported case numbers was assessed.

Methods

SARIMA models were fitted to describe reported weekly pertussis case numbers over a four-year period in Germany. Pertussis-related Google Trends data (GTD) was added as an external regressor. Predictions were made by the models, both with and without GTD, and compared with values within the validation dataset over a one-year and for a two-weeks period.

Results

Predictions of the traditional model using solely reported case numbers resulted in an RMSE (residual mean squared error) of 192.65 and 207.8, a mean absolute percentage error (MAPE) of 58.59 and 72.1, and a mean absolute error (MAE) 169.53 and 190.53 for the one-year and for the two-weeks period, respectively. The GTD expanded model achieved better forecasting accuracy (RMSE: 144.22 and 201.78), a MAPE 43.86, and 68.54 and a MAE of 124.46 and 178.96. Corrected Akaike Information Criteria also favored the GTD expanded model (1750.98 vs. 1746.73). The difference between the predictive performances was significant when using a two-sided Diebold-Mariano test (DM value: 6.86, p < 0.001) for the one-year period.

Conclusion

Internet-based surveillance data enhanced the predictive ability of a traditionally based model and should be considered as a method to enhance future disease modeling.

•

Pertussis-related Google Trends Data (GTD) showed a weak but significant correlation with the reported weekly number of pertussis cases.

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We fitted a SARIMA models to estimate reported weekly pertussis case numbers

•

The GTD-expanded models achieved significantly better predictive accuracy than the traditional model over a one-year-period.

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Corrected Akaike Information Criteria also favored the GTD-Expanded SARIMA model.

•

The use of GTD should be considered as a method to enhance pertussis forecasting.

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.

Incidence and severity of pertussis hospitalisations in infants aged less than 1 year in 37 hospitals of six EU/EEA countries, results of PERTINENT sentinel pilot surveillance system, December 2015 to December 2018

Introduction

PERTINENT is a pilot active surveillance system of infants hospitalised with pertussis in six European Union/European Economic Area countries (37 hospitals, seven sites).

Aim

This observational study aimed to estimate annual pertussis incidence per site from 2016 to 2018 and respective trends between 2017 and 2018. Pertussis cases were described, including their severity.

Methods

We developed a generic protocol and laboratory guidelines to harmonise practices across sites. Cases were hospitalised infants testing positive for Bordetella pertussis by PCR or culture. Sites collected demographic, clinical, laboratory data, vaccination status, and risk/protective factors. We estimated sites’ annual incidences by dividing case numbers by the catchment populations.

Results

From December 2015 to December 2018, we identified 469 cases (247 males; 53%). The median age, birthweight and gestational age were 2.5 months (range: 0–11.6; interquartile range (IQR): 2.5), 3,280 g (range: 700–4,925; IQR: 720) and 39 weeks (range: 25–42; IQR: 2), respectively. Thirty cases (6%) had atypical presentation either with cough or cyanosis only or with absence of pertussis-like symptoms. Of 330 cases with information, 83 (25%) were admitted to intensive care units including five deceased infants too young to be vaccinated. Incidence rate ratios between 2018 and 2017 were 1.43 in Czech Republic (p = 0.468), 0.25 in Catalonia (p = 0.002), 0.71 in France (p = 0.034), 0.14 in Ireland (p = 0.002), 0.63 in Italy (p = 0.053), 0.21 in Navarra (p = 0.148) and zero in Norway.

Conclusions

Incidence appeared to decrease between 2017 and 2018 in all but one site. Enhanced surveillance of hospitalised pertussis in Europe is essential to monitor pertussis epidemiology and disease burden.

Alarm Thresholds for Pertussis Outbreaks in Iran: National Data Analysis

Objectives

The purpose of the current study was to determine the upper threshold number of cases for which pertussis infection would reach an outbreak level nationally in Iran.

Methods

Data on suspected cases of pertussis from the 25^th February 2012 to the 23^rd March 2018 from the Center for Disease Control and Prevention in Iran was used. The national upper threshold level was estimated using the exponentially weighted moving average (EWMA) method and the Poisson regression method.

Results

In total, 2,577 (33.6%) and 1,714 (22.3%) cases were reported in the Spring and Summer respectively. There were 1,417 (18.5%) and 1,971 (25.6%) cases reported in the Autumn and Winter, respectively. The overall upper threshold using the EWMA and the Poisson regression methods, was estimated as a daily occurrence of 8 (7.55) and 7.50 (4.48–11.06) suspected cases per 10,000,000 people, respectively. The daily seasonal thresholds estimated by the EWMA and the Poisson regression methods were 10, 7, 6, 8 cases and 10, 7, 7, 9 cases for the Spring, Summer, Autumn, and Winter, respectively.

Conclusion

The overall and seasonal estimated thresholds by the 2 methods were similar. Therefore, the estimated thresholds of 6–10 cases in a day, per 10,000,000 people could be used to detect pertussis outbreaks and epidemics by health policymakers.

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.

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

BACKGROUND

After the introduction of a vaccine against B. pertussis the seasonal pattern with the highest number of infections in the spring to summer months changed. Recent studies from around the world suggest that B. pertussis infections again follow a seasonal pattern with increased incidence in summer.The aim of this study was to investigate whether respiratory infections caused by B. pertussis in the period from January 2008 to December 2018 also seasonally spread in Germany and if so, when the B. pertussis activity peaked.

METHODS

We tested 19,031 samples, mainly from Southern Germany, collected in the period from January 2008 to December 2018 using a Multiplex PCR assay. We assessed the number and proportion of samples positive for B. pertussis, stratified by patient's age and month. The seasonal distribution was investigated by plotting the average proportion of positive samples for each month.

RESULTS

We observed a B. pertussis seasonality with the highest number of positive samples in the months from June until September. In contrast, testing of samples for B. pertussis was requested most frequently in the period from October until March. The proportion of positive samples increased earlier in adolescents (age 10 to 19) than in other age groups.

CONCLUSIONS

We found a seasonality of B. pertussis infections in Germany, which differs from the time when most samples are sent in for testing of B. pertussis. Our study suggests that clinicians should be more aware of B. pertussis infections in the months from June until September to prevent further transmission to vulnerable family members.

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

Pertussis has resurged in many countries over recent years, especially among adolescents and adults. This study assessed the effect of weather variability on resurging pertussis among different age groups in Jinan, China. Data on weekly pertussis notifications by age group and weather factors (mean temperature (MeanT), mean temperature standard deviation within a week (MeanT SD), diurnal temperature range (DTR) and relative humidity (RH)) were collected between 2013 and 2017. Distributed lag non-linear models (DLNMs) and regression tree models were used to examine the non-linear association between weather variability and pertussis infections. The 2-weeks cumulative relative risk (RR) of pertussis infections was 4.46 (95% confidence interval (CI): 2.33-9.51) in 0-4 age group, 6.25 (95% CI: 1.38-22.76) in 5-9 age group and 10.11 (95% CI: 2.83-39.07) in 10+ age group when MeanT was at 30.0 °C. MeanT SD (RR range in the three age groups: 2.82-5.83), DTR (RR range: 6.33-11.56) and RH (RR range: 2.02-7.43) also exert significant influence, with the highest risks at 10+ age group. Regression tree models showed the interactive effects of weather variability. The mean pertussis infections increased by over 1.7-fold in 0-4 years group when MeanT ≥14 °C, RH ≥57% and DTR ≥10 °C; by over 2.3-fold in 5-9 years group when MeanT ≥20 °C and MeanT SD ≥3 °C; by 2.0-fold in 10+ years group when MeanT ≥0.7 °C, DTR ≥8.3 °C and RH ≥74%. The study found significantly different associations between weather variability and pertussis infections by age group, and appeared to be stronger in 10+ years group. Continuing climate change, together with other risk factors such as low antibody levels among adolescents and adults, may facilitate pertussis resurgence. This supports previous suggestions of carefully reconsidering current vaccination programme to effectively curb the resurgence of pertussis.

Estimating seasonal variation in Australian pertussis notifications from 1991 to 2016: evidence of spring to summer peaks

Unlike for many other respiratory infections, the seasonality of pertussis is not well understood. While evidence of seasonal fluctuations in pertussis incidence has been noted in some countries, there have been conflicting findings including in the context of Australia. We investigated this issue by analysing the seasonality of pertussis notifications in Australia using monthly data from January 1991 to December 2016. Data were made available for all states and territories in Australia except for the Australian Capital Territory and were stratified into age groups. Using a time-series decomposition approach, we formulated a generalised additive model where seasonality is expressed using cosinor terms to estimate the amplitude and peak timing of pertussis notifications in Australia. We also compared these characteristics across different jurisdictions and age groups. We found evidence that pertussis notifications exhibit seasonality, with peaks observed during the spring and summer months (November–January) in Australia and across different states and territories. During peak months, notifications are expected to increase by about 15% compared with the yearly average. Peak notifications for children <5 years occurred 1–2 months later than the general population, which provides support to the theory that older household members remain an important source of pertussis infection for younger children. In addition, our results provide a more comprehensive spatial picture of seasonality in Australia, a feature lacking in previous studies. Finally, our findings suggest that seasonal forcing may be useful to consider in future population transmission models of pertussis.

Resurgence of Pertussis Infections in Shandong, China: Space-Time Cluster and Trend Analysis

Although vaccination is effective in preventing infection, pertussis remains endemic worldwide, including China. To lead better targeted prevention strategies, we examined dynamics of spatial and temporal patterns of pertussis transmission in Shandong, China, from 2009 to 2017. We used space-time cluster analysis, logistic regression analysis, and regression tree model to detect the changes in spatial patterns of pertussis infections in Shandong Province, China, between periods (2009–2011, 2012–2014, and 2015–2017). The yearly pertussis incidence rates dramatically increased by 16.8 times from 2009 to 2017. Shifting patterns of peaks of pertussis infections were observed over both time (from June–July to August–September) and space (from Linyi to Jinan), with increasing RR from 4.1 (95% CI: 2.3–7.4) (2009–2011) to 6.1 (95% CI: 5.6–6.7) (2015–2017) and obvious coincidence of peak time. West Shandong had larger odds of increased infections over the study period (odds ratio: 1.52 [95% CI: 1.05–2.17]), and pertussis had larger odds of spreading to east (odds ratio: 2.32 [95% CI: 1.63–3.31]) and north (odds ratio: 1.69 [95% CI: 1.06–2.99]) over time. Regression tree model indicated that the mean difference in yearly average pertussis incidence between 2009–2011 and 2015–2017 increased by more than 4-fold when the longitudes of counties are < 118.0°E. The geographic expansion of pertussis infection may increase the risk of epidemic peaks, coinciding with increased infections in the future. The findings might offer evidence for targeting preventive measures to the areas most in need to minimize the impact of the disease.

Using big data to predict pertussis infections in Jinan city, China: a time series analysis

This study aims to use big data (climate data, internet query data and school calendar patterns (SCP)) to improve pertussis surveillance and prediction, and develop an early warning model for pertussis epidemics. We collected weekly pertussis notifications, SCP, climate and internet search query data (Baidu index (BI)) in Jinan, China between 2013 and 2017. Time series decomposition and temporal risk assessment were used for examining the epidemic features in pertussis infections. A seasonal autoregressive integrated moving average (SARIMA) model and regression tree model were developed to predict pertussis occurrence using identified predictors. Our study demonstrates clear seasonal patterns in pertussis epidemics, and pertussis activity was most significantly associated with BI at 2-week lag (r_BI = 0.73, p < 0.05), temperature at 1-week lag (r_temp = 0.19, p < 0.05) and rainfall at 2-week lag (r_rainfall = 0.27, p < 0.05). No obvious relationship between pertussis peaks and school attendance was found in the study. Pertussis cases were more likely to be temporally concentrated throughout the epidemics during the study period. SARIMA models with 2-week-lagged BI and 1-week-lagged temperature had better predictive performance (β_{search query} = 0.06, p = 0.02; β_temp = 0.16, p = 0.03) with large correlation coefficients (r = 0.67, p < 0.01) and low root mean squared error (RMSE) value (r = 3.59). The regression tree model identified threshold values of potential predictors (search query, climate and SCP) for pertussis epidemics. Our results showed that internet query in conjunction with social and climatic data can predict pertussis epidemics, which is a foundation of using such data to develop early warning systems.

Timeliness of immunisations in preterm infants in the Netherlands

BACKGROUND

In the Netherlands, preterm infants receive the immunisations at the same chronological age as recommended for term infants without correction for gestational age (GA). The aim of this paper was to describe the timeliness of the routine Dutch national immunisation schedule in preterm infants in their first year of life and to evaluate possible determinants of delay.

METHODS

Preterm infants were prospectively recruited between October 2015 and October 2017 and stratified according to GA (<28, 28-32 and 32-36 weeks). Data from the baseline parental questionnaire, monthly parental questionnaires and medical records were used to determine the immunisation age and proportion of infants timely receiving the first immunisations (between 42 and 63 days). Results were compared between the GA and birth weight (BW) groups. Determinants associated with timeliness of immunisation were studied by multivariate logistic regression analysis.

RESULTS

Timely start of immunisation occurs in 60.5% of preterm infants in the Netherlands. The proportion of infants receiving the first immunisation on time was lowest for the group with GA <28 weeks (37%). The mean age of the first immunisation across all GA groups was 62.7 days (range 33-118) and differed significantly between GA group <28 weeks and the other two GA groups of 28-32 and 32-36 weeks (p < 0.001). Similar results were seen when stratified by BW. Multivariate analysis showed that low socioeconomic status (SES) and prolonged hospitalisation beyond 37 weeks each negatively influenced timeliness of the first immunisation.

CONCLUSION

These findings indicate that start of immunisations was often delayed in prematures and differs for different GA groups, being lowest (37%) in infants <28 weeks GA. Lower SES and prolonged hospital stay beyond 37 weeks GA are important determinants of timeliness. Efforts to improve timeliness should focus most on counselling parents in lower SES.

Spatio-temporal comparison of pertussis outbreaks in Olmsted County, Minnesota, 2004-2005 and 2012: a population-based study

OBJECTIVE

Two pertussis outbreaks occurred in Olmsted County, Minnesota, during 2004-2005 and 2012 (5-10 times higher than other years), with significantly higher incidence than for the State. We aimed to assess whether there were similar spatio-temporal patterns between the two outbreaks.

SETTING

Olmsted County, Minnesota, USA PARTICIPANTS: We conducted a population-based retrospective cohort study of all Olmsted County residents during the 2004-2005 and 2012 outbreaks, including laboratory-positive pertussis cases.

PRIMARY OUTCOME MEASURE

For each outbreak, we estimated (1) age-specific incidence rate using laboratory-positive pertussis cases (numerator) and the Rochester Epidemiology Project Census (denominator), a medical record-linkage system for virtually all Olmsted County residents, and (2) pertussis case density using kernel density estimation to identify areas with high case density. To account for population size, we calculated relative difference of observed density and expected density based on age-specific incidence.

RESULTS

We identified 157 and 195 geocoded cases in 2004-2005 and 2012, respectively. Incidence was the highest among adolescents (ages 11 to <14 years) for both outbreaks (9.6 and 7.9 per 1000). The 2004-2005 pertussis outbreak had higher incidence in winter (52% of cases) versus summer in 2012 (53%). We identified a consistent area with higher incidence at the beginning (ie, first quartile) of two outbreaks, but it was inconsistent for later quartiles. The relative difference maps for the two outbreaks suggest a greater role of neighbourhood population size in 2012 compared with 2004-2005.

CONCLUSIONS

Comparing spatio-temporal patterns between two pertussis outbreaks identified a consistent geographical area with higher incidence of pertussis at the beginning of outbreaks in this community. This finding can be tested in future outbreaks, and, if confirmed, can be used for identifying epidemiological risk factors clustered in such areas for geographically targeted intervention.

Time series modeling of pertussis incidence in China from 2004 to 2018 with a novel wavelet based SARIMA-NAR hybrid model

BACKGROUND

It is a daunting task to discontinue pertussis completely in China owing to its growing increase in the incidence. While basic to any formulation of prevention and control measures is early response for future epidemic trends. Discrete wavelet transform(DWT) has been emerged as a powerful tool in decomposing time series into different constituents, which facilitates better improvement in prediction accuracy. Thus we aim to integrate modeling approaches as a decision-making supportive tool for formulating health resources.

METHODS

We constructed a novel hybrid method based on the pertussis morbidity cases from January 2004 to May 2018 in China, where the approximations and details decomposed by DWT were forecasted by a seasonal autoregressive integrated moving average (SARIMA) and nonlinear autoregressive network (NAR), respectively. Then, the obtained values were aggregated as the final results predicted by the combined model. Finally, the performance was compared with the SARIMA, NAR and traditional SARIMA-NAR techniques.

RESULTS

The hybrid technique at level 2 of db2 wavelet including a SARIMA(0,1,3)(1,0,0)12modelfor the approximation-forecasting and NAR model with 12 hidden units and 4 delays for the detail d1-forecasting, along with another NAR model with 11 hidden units and 5 delays for the detail d2-forecasting notably outperformed other wavelets, SARIMA, NAR and traditional SARIMA-NAR techniques in terms of the mean square error, root mean square error, mean absolute error and mean absolute percentage error. Descriptive statistics exhibited that a substantial rise was observed in the notifications from 2013 to 2018, and there was an apparent seasonality with summer peak. Moreover, the trend was projected to continue upwards in the near future.

CONCLUSIONS

This hybrid approach has an outstanding ability to improve the prediction accuracy relative to the others, which can be of great help in the prevention of pertussis. Besides, under current trend of pertussis morbidity, it is required to urgently address strategically within the proper policy adopted.

Bordetella pertussis Infection in South African HIV-Infected and HIV-Uninfected Mother-Infant Dyads: A Longitudinal Cohort Study

Background. There is a paucity of data regarding the burden of Bordetella pertussis in African women and young infants, and particularly the impact of maternal human immunodeficiency virus (HIV) infection thereon. We performed a retrospective analysis of respiratory illness samples from longitudinal cohorts of HIV-uninfected and HIV-infected women and their infants to evaluate the burden of pertussis illness in a black-African community.

Methods. The women were followed up for respiratory illness from midpregnancy and together with their infants until 24 weeks postpartum. Respiratory samples obtained at the time of illness visits were tested for B. pertussis by polymerase chain reaction (PCR).

Results. The study included 194 HIV-infected and 1060 HIV-uninfected women, and 188 and 1028 infant offspring, respectively. There were 7 PCR-confirmed pertussis cases in the HIV-exposed infants and 30 in HIV-unexposed infants (7.4 vs 5.5 episodes per 1000 infant-months; P = .47), at a mean age of 70.9 days. All infant pertussis cases had a history of cough (mean duration, 6.3 days). Six of 17 (35.3%) pertussis-confirmed cases in infants <2 months of age were admitted to hospital within 21 days of B. pertussis detection, whereas none of the 20 cases ≥2 months of age required hospitalization. Ten PCR-positive pertussis-associated illnesses were detected in HIV-infected women compared with 32 in the HIV-uninfected women (6.8 vs 3.9 episodes per 1000 person-months; P = .12).

Conclusions. Bordetella pertussis identification was common among young infants with respiratory illness, most of whom were too young to be fully protected through direct vaccination. Vaccination of pregnant women might be a valuable strategy in a setting such us ours to prevent B. pertussis–associated illness in women and their young infants.

Eight-Year Review of Bordetella pertussis Testing Reveals Seasonal Pattern in the United States

Review of Bordetella pertussis polymerase chain reaction testing from 2007 through 2014 revealed a yearly spike in positivity rates during the summer throughout the United States. Paradoxically, the highest test volumes occurred outside of this time frame, which provides an opportunity for improved test utilization.

Prevalence, diagnosis, and disease course of pertussis in adults with acute cough: a prospective, observational study in primary care

Background

Most cases of adult pertussis probably remain undiagnosed.

Aim

To explore the prevalence, diagnosis, and disease course of acute pertussis infection in adult patients presenting with acute cough.

Design and setting

Prospective observational study between 2007 and 2010 in primary care in 12 European countries.

Method

Adults presenting with acute cough (duration of ≤28 days) were included. Bordetella pertussis infection was determined by polymerase chain reaction (from nasopharyngeal flocked swabs and sputa) and by measurement of immunoglobulin G antibodies to pertussis toxin (PT) in venous blood at day 28. An antibody titre to PT of ≥125 IU/ml or PCR positive result in a respiratory sample defined recent infection. Patients completed a symptom diary for 28 days.

Results

Serum and/or respiratory samples were obtained in 3074 patients. Three per cent (93/3074) had recent B. pertussis infection. Prior cough duration >2 weeks discriminated to some extent between those with and without pertussis (adjusted odds ratio 1.89, 95% confidence interval = 1.17 to 3.07; P = 0.010). Median cough duration after presentation was 17 and 12 days in patients with and without pertussis, respectively (P = 0.008). Patients with pertussis had longer duration of phlegm production (P = 0.010), shortness of breath (P = 0.037), disturbed sleep (P = 0.013) and interference with normal activities or work (P = 0.033) after presentation.

Conclusion

Pertussis infection plays a limited role among adults presenting with acute cough in primary care, but GPs should acknowledge the possibility of pertussis in uncomplicated lower respiratory tract infection. As in children, pertussis also causes prolonged symptoms in adults. However, pertussis is difficult to discern from other acute cough syndromes in adults at first presentation.

Time series analysis of temporal trends in the pertussis incidence in Mainland China from 2005 to 2016

Short-term forecast of pertussis incidence is helpful for advanced warning and planning resource needs for future epidemics. By utilizing the Auto-Regressive Integrated Moving Average (ARIMA) model and Exponential Smoothing (ETS) model as alterative models with R software, this paper analyzed data from Chinese Center for Disease Control and Prevention (China CDC) between January 2005 and June 2016. The ARIMA (0,1,0)(1,1,1)₁₂ model (AICc = 1342.2 BIC = 1350.3) was selected as the best performing ARIMA model and the ETS (M,N,M) model (AICc = 1678.6, BIC = 1715.4) was selected as the best performing ETS model, and the ETS (M,N,M) model with the minimum RMSE was finally selected for in-sample-simulation and out-of-sample forecasting. Descriptive statistics showed that the reported number of pertussis cases by China CDC increased by 66.20% from 2005 (4058 cases) to 2015 (6744 cases). According to Hodrick-Prescott filter, there was an apparent cyclicity and seasonality in the pertussis reports. In out of sample forecasting, the model forecasted a relatively high incidence cases in 2016, which predicates an increasing risk of ongoing pertussis resurgence in the near future. In this regard, the ETS model would be a useful tool in simulating and forecasting the incidence of pertussis, and helping decision makers to take efficient decisions based on the advanced warning of disease incidence.

Pertussis: Microbiology, Disease, Treatment, and Prevention

Pertussis is a severe respiratory infection caused by Bordetella pertussis, and in 2008, pertussis was associated with an estimated 16 million cases and 195,000 deaths globally. Sizeable outbreaks of pertussis have been reported over the past 5 years, and disease reemergence has been the focus of international attention to develop a deeper understanding of pathogen virulence and genetic evolution of B. pertussis strains. During the past 20 years, the scientific community has recognized pertussis among adults as well as infants and children. Increased recognition that older children and adolescents are at risk for disease and may transmit B. pertussis to younger siblings has underscored the need to better understand the role of innate, humoral, and cell-mediated immunity, including the role of waning immunity. Although recognition of adult pertussis has increased in tandem with a better understanding of B. pertussis pathogenesis, pertussis in neonates and adults can manifest with atypical clinical presentations. Such disease patterns make pertussis recognition difficult and lead to delays in treatment. Ongoing research using newer tools for molecular analysis holds promise for improved understanding of pertussis epidemiology, bacterial pathogenesis, bioinformatics, and immunology. Together, these advances provide a foundation for the development of new-generation diagnostics, therapeutics, and vaccines.

Comparing Seasonal Pattern of Laboratory Confirmed Cases of Pertussis with Clinically Suspected Cases

Objectives

During recent decades, there has been limited attention on the seasonal pattern of pertussis within a high vaccine coverage population. This study aimed to compare the seasonal patterns of clinical suspected pertussis cases with those of laboratory confirmed cases in Iran.

Methods

The current study was conducted using time series methods. Time variables included months and seasons during 2011–2013. The effects of seasons and months on the incidence of pertussis were estimated using analysis of variance or Kruskal–Wallis.

Results

The maximum average incidence of clinically confirmed pertussis was 23.3 in July (p = 0.04), but the maximum incidence of clinical suspected pertussis was 115.7 in May (p = 0.6). The maximum seasonal incidences of confirmed and clinical pertussis cases were reported in summer (average: 12, p = 0.004), and winter (average: 108.1; p = 0.4), respectively.

Conclusion

The present study showed that the seasonal pattern of laboratory confirmed pertussis cases is highly definite and different from the pattern of clinical suspected cases.

Differences in Bordetella pertussis DNA load according to clinical and epidemiological characteristics of patients with whooping cough

OBJECTIVE

To identify associations between nasopharyngeal Bordetella pertussis DNA load and clinical and epidemiological characteristics and evaluate DNA load prognostic value in pertussis severity.

METHODS

Prospective observational multi-centre study including nasopharyngeal samples positive to pertussis DNA by real-time PCR collected from children and adult patients in more than 200 health centres of Catalonia (Spain) during 2012-2013.

RESULTS

B. pertussis load was inversely correlated with age (rho = -0.32, p < 0.001), time to diagnosis (rho = -0.33, p < 0.001) and number of symptoms (rho = 0.13, p = 0.002). Median bacterial load was significantly higher in inpatients versus outpatients (4.91 vs. 2.55 log10 CFU/mL, p < 0.001), patients with complications versus those without (6.05 vs. 2.82 log10 CFU/mL, p < 0.001), disease incidence in summer and autumn versus spring and winter (3.50 vs. 2.21 log10 CFU/mL, p = 0.002), and unvaccinated-partially vaccinated patients versus vaccinated (4.20 vs. 2.76 log10 CFU/mL, p = 0.004). A logistic regression model including bacterial load and other candidate prognostic factors showed good prediction for hospital care (AUC = 0.94) although only age and unvaccinated status were found to be prognostic factors.

CONCLUSIONS

We observed strong positive associations of nasopharyngeal bacterial load with severity outcomes of hospitalisation and occurrence of complications. Bacterial load and other independent variables contributed to an accurate prognostic model for hospitalisation.

An evidence synthesis approach to estimating the incidence of symptomatic pertussis infection in the Netherlands, 2005-2011

BACKGROUND

Despite high vaccination coverage, infection with Bordetella pertussis is a current public health concern in the Netherlands and other European Union member states. Because surveillance data are subject to extensive under-ascertainment and under-reporting, incidence is difficult to determine. Our objective was to estimate the age-group specific incidence of symptomatic pertussis infection in the Netherlands over the period 2005-2011, using multi-parameter evidence synthesis.

METHODS

Age-specific seroconversion probabilities were estimated for 2007 using Netherlands population data stratified by age-group and cross-sectional population-wide serosurvey (PIENTER-2) data, with a sero-diagnostic cut-off of 125 EU/ml as a proxy for recent infection. Symptomatic probabilities were derived from a study of household contacts and from PIENTER-2. The annual number of symptomatic infected (SI) persons was estimated using evidence synthesis methods in a Bayesian framework, by combining the estimated incidence of infection with notification data and symptomatic probabilities.

RESULTS

An incidence rate of 128 SI cases per 10,000 population (95 % credible interval [CrI]: 110-150) was estimated for 2005, which decreased to 107 per 10,000 (95 % CrI: 91-126) for 2011. The degree of underestimation in statutory notified cases was age-dependent, ranging from 10-fold (10-19 years) to 69-fold (60+ years). The largest annual decreases in SI incidence rate over the study period were in the 1-4 and 5-9 years age-groups (24.3 %, 15.9 % per year, respectively).

CONCLUSIONS

By synthesising all available data, the incidence of symptomatic pertussis and the extent to which SI is underrepresented by notification data can be estimated. Such estimates are essential for disease burden computation and for informing public health priority-setting.

Pertussis models to inform vaccine policy

Pertussis remains a challenging public health problem with many aspects of infection, disease and immunity poorly understood. Initially controlled by mass vaccination, pertussis resurgence has occurred in some countries with well-established vaccination programs, particularly among adolescents and young adults. Several studies have used mathematical models to investigate drivers of pertussis epidemiology and predict the likely impact of different vaccination strategies. We reviewed a number of these models to evaluate their suitability to answer questions of public health importance regarding optimal vaccine scheduling. We critically discuss the approaches adopted and the impact of chosen model structures and assumptions on study conclusions. Common limitations were a lack of contemporary, population relevant data for parameterization and a limited understanding of the relationship between infection and disease. We make recommendations for future model development and suggest epidemiologic data collections that would facilitate efforts to reduce uncertainty and improve the robustness of model-derived conclusions.

Dynamics of Pertussis Transmission in the United States

Past patterns of infectious disease transmission set the stage on which modern epidemiologic dynamics are played out. Here, we present a comprehensive account of pertussis (whooping cough) transmission in the United States during the early vaccine era. We analyzed recently digitized weekly incidence records from Morbidity and Mortality Weekly Reports from 1938 to 1955, when the whole-cell pertussis vaccine was rolled out, and related them to contemporary patterns of transmission and resurgence documented in monthly incidence data from the National Notifiable Diseases Surveillance System. We found that, during the early vaccine era, pertussis epidemics in US states could be categorized as 1) annual, 2) initially annual and later multiennial, or 3) multiennial. States with predominantly annual cycles tended to have higher per capita birth rates, more household crowding, more children per family, and lower rates of school attendance than the states with multiennial cycles. Additionally, states that exhibited annual epidemics during 1938-1955 have had the highest recent (2001-2010) incidence, while those states that transitioned from annual cycles to multiennial cycles have had relatively low recent incidence. Our study provides an extensive picture of pertussis epidemiology in the United States dating back to the onset of vaccination, a back-story that could aid epidemiologists in understanding contemporary transmission patterns.

The importance of climatic factors and outliers in predicting regional monthly campylobacteriosis risk in Georgia, USA

Incidence of Campylobacter infection exhibits a strong seasonal component and regional variations in temperate climate zones. Forecasting the risk of infection regionally may provide clues to identify sources of transmission affected by temperature and precipitation. The objectives of this study were to (1) assess temporal patterns and differences in campylobacteriosis risk among nine climatic divisions of Georgia, USA, (2) compare univariate forecasting models that analyze campylobacteriosis risk over time with those that incorporate temperature and/or precipitation, and (3) investigate alternatives to supposedly random walk series and non-random occurrences that could be outliers. Temporal patterns of campylobacteriosis risk in Georgia were visually and statistically assessed. Univariate and multivariable forecasting models were used to predict the risk of campylobacteriosis and the coefficient of determination (R(2)) was used for evaluating training (1999-2007) and holdout (2008) samples. Statistical control charting and rolling holdout periods were investigated to better understand the effect of outliers and improve forecasts. State and division level campylobacteriosis risk exhibited seasonal patterns with peaks occurring between June and August, and there were significant associations between campylobacteriosis risk, precipitation, and temperature. State and combined division forecasts were better than divisions alone, and models that included climate variables were comparable to univariate models. While rolling holdout techniques did not improve predictive ability, control charting identified high-risk time periods that require further investigation. These findings are important in (1) determining how climatic factors affect environmental sources and reservoirs of Campylobacter spp. and (2) identifying regional spikes in the risk of human Campylobacter infection and their underlying causes.

Epidemiological aspects of pertussis among adults and adolescents in a Korean outpatient setting: a multicenter, PCR-based study

Epidemiological data of Bordetella pertussis infection among adolescents and adults are limited in Korea. Patients (≥ 11 yr of age) with a bothersome cough for less than 30 days were enrolled during a 1-yr period at 22 hospitals in Korea. Nasopharyngeal swabs were collected for polymerase chain reaction (PCR) and for bacteriologic culture. In total, 490 patients were finally enrolled, and 34 (6.9%) patients tested positive for B. pertussis; cough duration (14.0 days [7.0-21.0 days]) and age distribution were diverse. The incidence was the highest in secondary referral hospitals, compared to primary care clinics or tertiary referral hospitals (24/226 [10.6%] vs. 3/88 [3.4%] vs. 7/176 [4.0%], P = 0.012), and the peak incidence was observed in February and August (15.8% and 15.9%), with no confirmed cases between March and June. In the multivariate analysis, post-tussive vomiting was significantly associated with pertussis (odds ratio, 2.508; 95% confidence interval, 1.146-5.486) and secondary referral hospital showed a borderline significance. In conclusion, using a PCR-based method, 6.9% of adolescent and adult patients with an acute cough illness had pertussis infection in an outpatient setting. However, hospital levels and seasonal trends must be taken into account to develop a better strategy for controlling pertussis.

Immune boosting explains regime-shifts in prevaccine-era pertussis dynamics

Understanding the biological mechanisms underlying episodic outbreaks of infectious diseases is one of mathematical epidemiology’s major goals. Historic records are an invaluable source of information in this enterprise. Pertussis (whooping cough) is a re-emerging infection whose intermittent bouts of large multiannual epidemics interspersed between periods of smaller-amplitude cycles remain an enigma. It has been suggested that recent increases in pertussis incidence and shifts in the age-distribution of cases may be due to diminished natural immune boosting. Here we show that a model that incorporates this mechanism can account for a unique set of pre-vaccine-era data from Copenhagen. Under this model, immune boosting induces transient bursts of large amplitude outbreaks. In the face of mass vaccination, the boosting model predicts larger and more frequent outbreaks than do models with permanent or passively-waning immunity. Our results emphasize the importance of understanding the mechanisms responsible for maintaining immune memory for pertussis epidemiology.

Comparison of time series models for predicting campylobacteriosis risk in New Zealand

Predicting campylobacteriosis cases is a matter of considerable concern in New Zealand, after the number of the notified cases was the highest among the developed countries in 2006. Thus, there is a need to develop a model or a tool to predict accurately the number of campylobacteriosis cases as the Microbial Risk Assessment Model used to predict the number of campylobacteriosis cases failed to predict accurately the number of actual cases. We explore the appropriateness of classical time series modelling approaches for predicting campylobacteriosis. Finding the most appropriate time series model for New Zealand data has additional practical considerations given a possible structural change, that is, a specific and sudden change in response to the implemented interventions. A univariate methodological approach was used to predict monthly disease cases using New Zealand surveillance data of campylobacteriosis incidence from 1998 to 2009. The data from the years 1998 to 2008 were used to model the time series with the year 2009 held out of the data set for model validation. The best two models were then fitted to the full 1998-2009 data and used to predict for each month of 2010. The Holt-Winters (multiplicative) and ARIMA (additive) intervention models were considered the best models for predicting campylobacteriosis in New Zealand. It was noticed that the prediction by an additive ARIMA with intervention was slightly better than the prediction by a Holt-Winter multiplicative method for the annual total in year 2010, the former predicting only 23 cases less than the actual reported cases. It is confirmed that classical time series techniques such as ARIMA with intervention and Holt-Winters can provide a good prediction performance for campylobacteriosis risk in New Zealand. The results reported by this study are useful to the New Zealand Health and Safety Authority's efforts in addressing the problem of the campylobacteriosis epidemic.

Diagnostic value of symptoms and laboratory data for pertussis in adolescent and adult patients

Background

Several symptoms are classically thought to be suggestive of pertussis in children, but the diagnostic value of these symptoms in adolescent and adult patients is unclear. We evaluated the accuracy of the clinical findings for the early presumptive diagnosis of pertussis in adolescent and adult patients. Furthermore, we measured fractional exhaled nitric oxide (FeNO) with regard to whether we could distinguish eosinophilic inflammation of the airway and pertussis. FeNO is not expected to be associated with pertussis.

Methods

We compared 183 cases with laboratory-confirmed pertussis using serology and polymerase chain reaction and 1,132 cases without laboratory-confirmed pertussis.

Results

Among pertussis patients, paroxysmal cough was common with 90% sensitivity, but the specificity was low (25%). Posttussive vomiting and whoop were less common (sensitivity 25% and 19%, respectively), but both showed greater specificity for pertussis (80% and 86%, respectively). Posttussive gagging was observed with intermediate frequency and provided greater specificity (49% and 77%, respectively). Pertussis cases were most frequent between May and August with a peak in June. The mean FeNO value for the pertussis patients was 18.2 ± 9.2 ppb, which was significantly lower than that in asthma patients (56.9 ± 20.3 ppb, p <0.001). The most useful definition was posttussive vomiting and/or gagging, and a plus normal FeNO value, which had a sensitivity of 72% and a specificity of 70%.

Conclusions

Clinical symptoms and laboratory data are of limited value in making the diagnosis of pertussis, and it was clinically difficult to differentiate adolescent and adult patients with or without pertussis. However, pertussis should be considered if patients have posttussive vomiting and/or gagging and a normal FeNO concentration.

Methods to assess seasonal effects in epidemiological studies of infectious diseases--exemplified by application to the occurrence of meningococcal disease

Seasonal variation in occurrence is a common feature of many diseases, especially those of infectious origin. Studies of seasonal variation contribute to healthcare planning and to the understanding of the aetiology of infections. In this article, we provide an overview of statistical methods for the assessment and quantification of seasonality of infectious diseases, as exemplified by their application to meningococcal disease in Denmark in 1995-2011. Additionally, we discuss the conditions under which seasonality should be considered as a covariate in studies of infectious diseases. The methods considered range from the simplest comparison of disease occurrence between the extremes of summer and winter, through modelling of the intensity of seasonal patterns by use of a sine curve, to more advanced generalized linear models. All three classes of method have advantages and disadvantages. The choice among analytical approaches should ideally reflect the research question of interest. Simple methods are compelling, but may overlook important seasonal peaks that would have been identified if more advanced methods had been applied. For most studies, we suggest the use of methods that allow estimation of the magnitude and timing of seasonal peaks and valleys, ideally with a measure of the intensity of seasonality, such as the peak-to-low ratio. Seasonality may be a confounder in studies of infectious disease occurrence when it fulfils the three primary criteria for being a confounder, i.e. when both the disease occurrence and the exposure vary seasonally without seasonality being a step in the causal pathway. In these situations, confounding by seasonality should be controlled as for any confounder.

The Collaborative Pediatric Critical Care Research Network Critical Pertussis Study: collaborative research in pediatric critical care medicine

OBJECTIVE

To provide an updated overview of critical pertussis to the pediatric critical care community and describe a study of critical pertussis recently undertaken.

SETTING

The six sites, seven hospitals of the Collaborative Pediatric Critical Care Research Network, and 17 outside sites at academic medical centers with pediatric intensive care units.

RESULTS

Despite high coverage for childhood vaccination, pertussis causes substantial morbidity and mortality in US children, especially among infants. In pediatric intensive care units, Bordetella pertussis is a community-acquired pathogen associated with critical illness and death. The incidence of medical and developmental sequelae in critical pertussis survivors remains unknown, and the appropriate strategies for treatment and support remain unclear. The Collaborative Pediatric Critical Care Research Network Critical Pertussis Study has begun to evaluate critical pertussis in a prospective cohort.

CONCLUSION

Research is urgently needed to provide an evidence base that might optimize management for critical pertussis, a serious, disabling, and too often fatal illness for U.S. children and those in the developing world.

Cost-effectiveness analysis of various pertussis vaccination strategies primarily aimed at protecting infants in the Netherlands

BACKGROUND

Pertussis is a highly contagious respiratory disease. Despite a high rate of vaccine coverage through the Dutch national immunization program, the incidence of pertussis remains high in the Netherlands and the risk of infection continues. Because pertussis is most severe in unimmunized infants and infants who have only received some of the recommended doses, new pertussis immunization strategies should be considered to protect this vulnerable population.

OBJECTIVE

This study was designed to estimate the cost-effectiveness of 3 new immunization strategies for possible addition to the current Dutch national immunization program: immunization of the infant at birth, immunization of the parents immediately after birth of the child (cocooning), and maternal immunization during the third trimester of pregnancy.

METHODS

A literature search was performed in the PubMed database for articles published in English, German, and Dutch using the following terms: pertussis, whooping cough, vaccination strategies, maternal immunization, cocooning, at birth, vaccine efficacy, mortality, underreporting, prevalence, incidence, and cost-effectiveness. A decision-tree model was developed for this analysis, and data on pertussis morbidity and costs were collected consistently for different age groups (infants <1 year of age and adults 25 to 34 years of age). The size of the infant cohort was set at 200,000 to approximate previous Dutch birth cohorts. The size of the adult cohort was set at 401,380 parents for the cocooning strategy and 201,380 mothers for the maternal immunization strategy. Health benefits (quality-adjusted life-years [QALYs]) and costs were estimated in both cohorts for each of the 3 immunization strate- gies. Incremental cost-effectiveness ratios were calculated from both a payer's and a societal perspective. The robustness of the results was determined through sensitivity analysis.

RESULTS

In the base-case analysis, cocooning and maternal immunization were found to be effective in reducing the incidence of pertussis among infants (123 and 174 infant cases were expected to be prevented, respectively). Furthermore, cocooning and maternal immunization were estimated to be cost-effective from a payer's perspective (euro4600 [US $6400]/QALY and euro3500 [$4900]/QALY, respectively) and even cost-saving from a societal perspective (savings of up to euro7200 [$10,100] and euro5000 [$7000], respectively). Sensitivity analyses revealed that favorable cost-effectiveness was generally robust. In the sensitivity analysis, the cost-effectiveness of cocooning and maternal immunization was mostly sensitive for changes in assumptions on underreporting (200-fold increase in reported number of symptomatic cases) of pertussis disease and infection. With no underreporting, the ICER was estimated at euro211,900 ($296,700)/QALY for cocooning and euro81,600 ($114,200)/QALY for maternal immunization from a payer's perspective. However, even at much lower levels of underreporting (20- to 30-fold increase in incidence), cost-effectiveness remained favorable. The cost-effectiveness of the third strategy, at-birth immunization, was highly unfavorable (euro329,900 [$461,900]/QALY from a payer's perspective and euro330,100 [$462,100]/ QALY from a societal perspective).

CONCLUSIONS

This study estimated that the addition of cocooning or maternal immunization to the current Dutch national immunization program likely would be cost-effective or even cost-saving. These estimates were mainly due to reduction in the number of cases among parents, which are likely to be mild and therefore would largely remain unreported. Immunization at birth was not a cost-effective strategy. Cocooning was the most expensive intervention to implement; however, it resulted in the highest number of QALYs gained (mainly in adults). Maternal immunization would offer better protection of infants, due to maternally acquired antibodies.

Seroprevalence of pertussis in The Netherlands: evidence for increased circulation of Bordetella pertussis

BACKGROUND

In many countries, the reported pertussis has increased despite high vaccination coverage. However, accurate determination of the burden of disease is hampered by reporting artifacts. The infection frequency is more reliably estimated on the basis of the prevalence of high IgG concentrations against pertussis toxin (IgG-Ptx). We determined whether the increase in reported pertussis in the last decade is associated with an increase in the number of infections.

METHODOLOGY/PRINCIPAL FINDINGS

In a cross-sectional population-based serosurveillance study conducted in 2006-07, from a randomly selected age-stratified sample of 7,903 persons, serum IgG-Ptx concentrations were analyzed using a fluorescent bead-based multiplex immuno assay. In 2006-07, 9.3% (95%CI 8.5-10.1) of the population above 9 years of age had an IgG-Ptx concentration above 62.5 EU/ml (suggestive for pertussis infection in the past year), which was more than double compared to 1995-96 (4.0%; 95%CI 3.3-4.7). The reported incidence showed a similar increase as the seroprevalence between both periods.

CONCLUSIONS

Although changes in the vaccination program have reduced pertussis morbidity in childhood, they have not affected the increased infection rate in adolescent and adult pertussis. Indeed, the high circulation of B. pertussis in the latter age-categories may limit the effectiveness of pediatric vaccination.

Imperfect vaccine-induced immunity and whooping cough transmission to infants

Whooping cough, caused by B. pertussis and B. parapertussis, has increased in incidence throughout much of the developed world since the 1980s despite high vaccine coverage, causing an increased risk of infection in infants who have substantial disease-induced mortality. Duration of immunity and epidemically significant routes of transmission across age groups remain unclear and deserve further investigation to inform vaccination strategies to better control pertussis burden. The authors analyze age- and species-specific whooping cough tests and vaccine histories in Massachusetts from 1990 to 2008. On average, the disease-free duration is 10.5 years. However, it has been decreasing over time, possibly due to a rising force of infection through increased circulation. Despite the importance of teenage cases during epidemics, wavelet analyses suggest that they are not the most important source of transmission to infants. In addition, the data indicate that the B. pertussis vaccine is not protective against disease induced by B. parapertussis.

Transplacental transport of IgG antibodies specific for pertussis, diphtheria, tetanus, haemophilus influenzae type b, and Neisseria meningitidis serogroup C is lower in preterm compared with term infants

BACKGROUND

Maternal antibodies, transported through the placenta during pregnancy, contribute to the protection of infants from infectious diseases during the first months of life. The aim of this study was to measure the concentration of antibodies against several vaccine-preventable diseases in paired maternal and cord blood serum samples in preterm and term infants and to assess placental transfer ratios and infant antibody concentrations against vaccine-preventable diseases.

METHODS

Antibody concentrations specific against pertussis proteins (pertussis toxin, filamentous hemagglutinin, pertactin, and fimbriae), diphtheria and tetanus toxins, and antibody concentrations specific against polysaccharides from Haemophilus influenzae type b and Neisseria meningitidis serogroup C were measured in cord blood samples from preterm (<32 weeks and 1500 g) and term infants and maternal serum samples, using a fluorescent bead-based multiplex immunoassay.

RESULTS

A total of 96 preterm and 42 term infants and their mothers were included in the study. Placental transfer ratios of antibodies against all vaccine antigens were significantly lower in preterm infants (medians varied from 0.26 to 0.86) compared with term infants (medians, 0.74-1.89; all antibodies P < 0.05). Furthermore, polysaccharide-vaccine-specific antibodies showed lower transplacental transport ratios than protein-vaccine-specific antibodies. Maternal concentrations are the most important determinants of infant antibody concentrations against vaccine-preventable diseases.

CONCLUSIONS

Preterm infants benefit to a lesser extent from maternal antibodies against vaccine-preventable diseases than term infants, posing them at higher risk for infectious diseases in the first months of life.

Incidence and reproduction numbers of pertussis: estimates from serological and social contact data in five European countries

BACKGROUND

Despite large-scale vaccination programmes, pertussis has remained endemic in all European countries and has been on the rise in many countries in the last decade. One of the reasons that have been discussed for the failure of vaccination to eliminate the disease is continued circulation of the pathogen Bordetella pertussis by mostly asymptomatic and mild infections in adolescents and adults. To understand the impact of asymptomatic and undiagnosed infection on the transmission dynamics of pertussis we analysed serological data from five European countries in combination with information about social contact patterns from five of those countries to estimate incidence and reproduction numbers.

METHODS AND FINDINGS

We compared two different methods for estimating incidence from individual data on IgG pertussis toxin (PT) titres. One method combines the cross-sectional surveys of titres with longitudinal information about the distribution of amplitude and decay rate of titres in a back-calculation approach. The second method uses age-dependent contact matrices and cross-sectional surveys of IgG PT titres to estimate a next generation matrix for pertussis transmission among age groups. The next generation approach allows for computation of basic reproduction numbers for five European countries. Our main findings are that the seroincidence of infections as estimated with the first method in all countries lies between 1% and 6% per annum with a peak in the adolescent age groups and a second lower peak in young adults. The incidence of infections as estimated by the second method lies slightly lower with ranges between 1% and 4% per annum. There is a remarkably good agreement of the results obtained with the two methods. The basic reproduction numbers are similar across countries at around 5.5.

CONCLUSIONS

Vaccination with currently used vaccines cannot prevent continued circulation and reinfection with pertussis, but has shifted the bulk of infections to adolescents and adults. If a vaccine conferring lifelong protection against clinical and subclinical infection were available pertussis could be eliminated. Currently, continuing circulation of the pathogen at a subclinical level provides a refuge for the pathogen in which it can evolve and adjust to infect vaccinated populations. Please see later in the article for the Editors' Summary.

Comparison of three time-series models for predicting campylobacteriosis risk

Three time-series models (regression, decomposition, and Box-Jenkins autoregressive integrated moving averages) were applied to national surveillance data for campylobacteriosis with the goal of disease forecasting in three US states. Datasets spanned 1998-2007 for Minnesota and Oregon, and 1999-2007 for Georgia. Year 2008 was used to validate model results. Mean absolute percent error, mean square error and coefficient of determination (R2) were the main evaluation fit statistics. Results showed that decomposition best captured the temporal patterns in disease risk. Training dataset R2 values were 72.2%, 76.3% and 89.9% and validation year R2 values were 66.2%, 52.6% and 79.9% respectively for Georgia, Oregon and Minnesota. All three techniques could be utilized to predict monthly risk of infection for Campylobacter sp. However, the decomposition model provided the fastest, most accurate, user-friendly method. Use of this model can assist public health personnel in predicting epidemics and developing disease intervention strategies.