Solar radiation and water vapor pressure to forecast chickenpox epidemics

Hervás, Daniel; Hervás-Masip, J.; Nicolau, Alexandru; Reina, Jordi; Hervás, Juan A.

doi:10.1007/s10096-014-2243-3

Cited by 14 publications

(5 citation statements)

References 33 publications

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“…A possible explanation for this might be that longer periods of sunshine correspond to higher doses of solar radiation. Hervás et al [ 33 ] found that the effects of solar radiation, directly on the host immune system and/or indirectly through vitamin D metabolism, may play a role in varicella epidemics [ 32 ]. Another possible explanation for this might be that longer periods of sunshine correspond to more time for human activities outdoors where exposure to VZV is more likely.…”

Section: Discussionmentioning

confidence: 99%

Association between the incidence of varicella and meteorological conditions in Jinan, Eastern China, 2012–2014

et al. 2016

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BackgroundVaricella remains an important public health issue in China. In this study we explored the effect of weather conditions on the incidence of varicella in the temperate city of Jinan, Eastern China during 2012–2014 to inform public health prevention and control measures.MethodsData on reported cases of varicella were obtained from National Notifiable Disease Report System. Meteorological data for the same time period were obtained from the Jinan Meteorological Bureau. A negative binomial regression model was used to assess the relationships between meteorological variables and the incidence of varicella. Given collinearity between average temperature and atmospheric pressure, separate models were constructed: one including average temperature without atmospheric pressure, the other including atmospheric pressure but without average temperature. Both models included relative humidity, wind velocity, rainfall, sunshine, and year as independent variables.ResultsAnnual incidence rates of varicella were 44.47, 53.69, and 46.81 per 100,000 for 2012, 2013, and 2014, respectively. Each increase of 100 Pa (hPa) in atmospheric pressure was estimated to be associated with an increase in weekly incidence of 3.35 % (95 % CI = 2.94–3.67 %), while a 1 °C rise in temperature was associated with a decrease of 3.44 % (95 % CI = −3.73–3.15 %) in the weekly incidence of varicella. Similarly, a 1 % rise in relative humidity corresponded to a decrease of 0.50 % or 1.00 %, a 1 h rise in sunshine corresponded to an increase of 1.10 % or 0.50 %, and a 1 mm rise in rainfall corresponded to an increase of 0.20 % or 0.30 %, in the weekly incidence of varicella cases, depending on the variable considered in the model.ConclusionOur findings show that weather factors have a significant influence on the incidence of varicella. Meteorological conditions should be considered as important predictors of varicella incidence in Jinan, Eastern China.

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Section: Discussionmentioning

confidence: 99%

Association between the incidence of varicella and meteorological conditions in Jinan, Eastern China, 2012–2014

et al. 2016

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“…Specific models have been designed for diseases such as measles,[ 7 ] rubella, chickenpox,[ 8 ] dengue fever,[ 9 ] whooping cough,[ 10 ] smallpox,[ 11 ] malaria,[ 12 ] HIV/AIDS [ 13 ] and others. [ 14 ] Most models take the basic reproduction number R0 of the causative agent, defined as the threshold quantity that determines when an infection can invade and persist in a new host population, as one of the main assets.…”

Section: Introductionmentioning

confidence: 99%

Real-time predictive seasonal influenza model in Catalonia, Spain

Basile¹,

Fuente

Torner³

et al. 2018

PLoS ONE

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Influenza surveillance is critical to monitoring the situation during epidemic seasons and predictive mathematic models may aid the early detection of epidemic patterns. The objective of this study was to design a real-time spatial predictive model of ILI (Influenza Like Illness) incidence rate in Catalonia using one- and two-week forecasts. The available data sources used to select explanatory variables to include in the model were the statutory reporting disease system and the sentinel surveillance system in Catalonia for influenza incidence rates, the official climate service in Catalonia for meteorological data, laboratory data and Google Flu Trend. Time series for every explanatory variable with data from the last 4 seasons (from 2010–2011 to 2013–2014) was created. A pilot test was conducted during the 2014–2015 season to select the explanatory variables to be included in the model and the type of model to be applied. During the 2015–2016 season a real-time model was applied weekly, obtaining the intensity level and predicted incidence rates with 95% confidence levels one and two weeks away for each health region. At the end of the season, the confidence interval success rate (CISR) and intensity level success rate (ILSR) were analysed. For the 2015–2016 season a CISR of 85.3% at one week and 87.1% at two weeks and an ILSR of 82.9% and 82% were observed, respectively. The model described is a useful tool although it is hard to evaluate due to uncertainty. The accuracy of prediction at one and two weeks was above 80% globally, but was lower during the peak epidemic period. In order to improve the predictive power, new explanatory variables should be included.

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“…School closure, on the other hand, has been demonstrated to decrease respiratory morbidity during an influenza outbreak in Israel (Heymann et al in 2004). Likewise, an inverse association was observed between the number of varicella cases and school holidays in Mallorca (Spain) (Hervás et al 2015). However, the impact of schooling on bacterial infections is less known, and the association between GAS pharyngitis and schooling has not been evaluated.…”

Section: Introductionmentioning

confidence: 99%

Effects of meteorologic factors and schooling on the seasonality of group A streptococcal pharyngitis

et al. 2015

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The objective of this study was to determine the seasonal pattern of group A streptococcal pharyngitis in children attended at a hospital emergency department in the Mediterranean island of Mallorca (Spain), and its association with meteorologic factors and schooling. We conducted a retrospective review of the medical records of children aged 1-15 years with a diagnosis of Streptococcus pyogenes pharyngitis between January 2006 and December 2011. The number of S. pyogenes pharyngitis was correlated to temperature, humidity, rainfall, atmospheric pressure, wind speed, solar radiation, and schooling, using regression and time series techniques. A total of 906 patients (median, 4 years old) with S. pyogenes pharyngitis, confirmed by throat culture, were attended during the study period. A seasonal pattern was observed with a peak activity in June and a minimum in September. Mean temperature, solar radiation, and school holidays were the best predicting variables (R(2) = 0.68; p < 0.001). S. pyogenes activity increased with the decrease of mean temperature (z = -2.4; p < 0.05), the increase of solar radiation (z = 4.2; p < 0.001), and/or the decrease in school holidays (z = -2.4; p < 0.05). In conclusion, S. pyogenes pharyngitis had a clear seasonality predominating in springtime, and an association with mean temperature, solar radiation, and schooling was observed. The resulting model predicted 68 % of S. pyogenes pharyngitis.

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Solar radiation and water vapor pressure to forecast chickenpox epidemics

Cited by 14 publications

References 33 publications

Association between the incidence of varicella and meteorological conditions in Jinan, Eastern China, 2012–2014

Association between the incidence of varicella and meteorological conditions in Jinan, Eastern China, 2012–2014

Real-time predictive seasonal influenza model in Catalonia, Spain

Effects of meteorologic factors and schooling on the seasonality of group A streptococcal pharyngitis

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