Indirect transmission and the effect of seasonal pathogen inactivation on infectious disease periodicity

On modelling airborne infection risk

Airborne infection risk analysis is usually performed for enclosed spaces where susceptible individuals are exposed to infectious airborne respiratory droplets by inhalation. It is usually based on exponential, dose-response models of which a widely used variant is the Wells-Riley (WR) model. We revisit this infection-risk estimate and extend it to the population level. We use an epidemiological model where the mode of pathogen transmission, airborne or contact, is explicitly considered. We illustrate the link between epidemiological models and the WR and the Gammaitoni and Nucci models. We argue that airborne infection quanta are, up to an overall density, airborne infectious respiratory droplets modified by a parameter that depends on biological properties of the pathogen, physical properties of the droplet and behavioural properties of the individual. We calculate the time-dependent risk of being infected for two scenarios. We show how the epidemic infection risk depends on the viral latent period and the event time, the time infection occurs. Infection risk follows the dynamics of the infected population. As the latent period decreases, infection risk increases. The longer a susceptible is present in the epidemic, the higher its risk of infection for equal exposure time to the pathogen is.

Effect of enterovirus 71 vaccination on the epidemiological characteristics and etiology in hospitalized children with hand-foot-and-mouth disease: A retrospective study from a tertiary children's hospital

Enterovirus 71 (EV71) vaccine for hand-foot-and-mouth disease (HFMD) prevention has been available for several years. However, as a new vaccine, the impact of EV71 vaccination on the epidemiology and etiology of HFMD is currently unclear. The purpose of this study was to compare and analyze the changes of epidemiological characteristics and etiology of HFMD patients after the introduction of EV71 vaccine. The data of hospitalized children with HFMD from 2014 to 2020 were collected from the case record department of a tertiary children hospital of Anhui Province. The changes of epidemiological characteristics, time distribution, disease severity and enterovirus serotypes in hospitalized children were analyzed. A total of 7373 cases of HFMD were reported during 2014 to 2020, including 634 (8.6%) severe cases. The number of cases reached the peak in 2016 (n = 1783) and decreased gradually after EV71 vaccination. The results of etiological test showed the positive rate was 80.5%, in which EV71 accounted for 1599 (21.7%) and CV-A16 accounted for 1028 (13.9%) respectively. The number of patients showed a bimodal distribution throughout the year, which were April to June and October to November. The age distribution changed significantly following the introduction of EV71 vaccine. The proportion of 1-year-old group of post-vaccination was significantly higher than that of pre-vaccination (61.9% vs 50.8%, P < .001). The proportion of HFMD caused by EV71 and severe cases decreased significantly after the vaccination (P < .001 for both). While the comparison of epidemiological characteristics and enterovirus serotypes between unvaccinated and vaccinated cases during 2017 to 2020 showed no significant difference. The dominant enterovirus serotypes of hospitalized HFMD changed significantly after the introduction of EV71 vaccine. The proportion of severe cases decreased significantly after the vaccination, but EV71 was still a major pathogen in patients with severe HFMD. More age-appropriate children are recommended to get vaccinated to establish stronger herd immunity in the population.

Cryptocurrency as Epidemiologically Safe Means of Transactions: Diminishing Risk of SARS-CoV-2 Spread

In comparison with other respiratory viruses, the current COVID-19 pandemic’s rapid seizing the world can be attributed to indirect (contact) way of transmission of SARS-CoV-2 virus in addition to the regular airborne way. A significant part of indirect transmission is made through cash bank notes. SARS-CoV-2 remains on cash paper money for period around four times larger than influenza A virus and is absorbed by cash notes two and a half times more effectively than influenza A (our model). During the pandemic, cryptocurrencies have gained attractiveness as an “epidemiologically safe” means of transactions. On the basis of the authors’ gallop polls performed online with social networks users in 44 countries in 2020–2021 (the total number of clear responses after the set repair 32,115), around 14.7% of surveyed participants engaged in cryptocurrency-based transactions during the pandemic. This may be one of the reasons of significant rise of cryptocurrencies rates since mid-March 2020 till the end of 2021. The paper discusses the reasons for cryptocurrency attractiveness during the COVID-19 pandemic. Among them, there are fear of SARS-CoV-2 spread via cash contacts and the ability of the general population to mine cryptocurrencies. The article also provides a breakdown of the polled audience profile to determine the nationalities that have maximal level of trust to saving and transacting money as cryptocurrencies.

How to Determine the Early Warning Threshold Value of Meteorological Factors on Influenza through Big Data Analysis and Machine Learning

Infectious diseases are a major health challenge for the worldwide population. Since their rapid spread can cause great distress to the real world, in addition to taking appropriate measures to curb the spread of infectious diseases in the event of an outbreak, proper prediction and early warning before the outbreak of the threat of infectious diseases can provide an important basis for early and reasonable response by the government health sector, reduce morbidity and mortality, and greatly reduce national losses. However, if only traditional medical data is involved, it may be too late or too difficult to implement prediction and early warning of an infectious outbreak. Recently, medical big data has become a research hotspot and has played an increasingly important role in public health, precision medicine, and disease prediction. In this paper, we focus on exploring a prediction and early warning method for influenza with the help of medical big data. It is well known that meteorological conditions have an influence on influenza outbreaks. So, we try to find a way to determine the early warning threshold value of influenza outbreaks through big data analysis concerning meteorological factors. Results show that, based on analysis of meteorological conditions combined with influenza outbreak history data, the early warning threshold of influenza outbreaks could be established with reasonable high accuracy.

Spatiotemporal Distribution of Hand, Foot, and Mouth Disease in Guangdong Province, China and Potential Predictors, 2009⁻2012

Background: Hand, foot, and mouth disease (HFMD) is a common infectious disease among children. Guangdong Province is one of the most severely affected provinces in south China. This study aims to identify the spatiotemporal distribution characteristics and potential predictors of HFMD in Guangdong Province and provide a theoretical basis for the disease control and prevention. Methods: Case-based HFMD surveillance data from 2009 to 2012 was obtained from the China Center for Disease Control and Prevention (China CDC). The Bayesian spatiotemporal model was used to evaluate the spatiotemporal variations of HFMD and identify the potential association with meteorological and socioeconomic factors. Results: Spatially, areas with higher relative risk (RR) of HFMD tended to be clustered around the Pearl River Delta region (the mid-east of the province). Temporally, we observed that the risk of HFMD peaked from April to July and October to December each year and detected an upward trend between 2009 and 2012. There was positive nonlinear enhancement between spatial and temporal effects, and the distribution of relative risk in space was not fixed, which had an irregular fluctuating trend in each month. The risk of HFMD was significantly associated with monthly average relative humidity (RR: 1.015, 95% CI: 1.006–1.024), monthly average temperature (RR: 1.045, 95% CI: 1.021–1.069), and monthly average rainfall (RR: 1.004, 95% CI: 1.001–1.008), but not significantly associated with average GDP. Conclusions: The risk of HFMD in Guangdong showed significant spatiotemporal heterogeneity. There was spatiotemporal interaction in the relative risk of HFMD. Adding a spatiotemporal interaction term could well explain the change of spatial effect with time, thus increasing the goodness of fit of the model. Meteorological factors, such as monthly average relative humidity, monthly average temperature, and monthly average rainfall, might be the driving factors of HFMD.

In vitro effect of Porphyromonas gingivalis combined with influenza A virus on respiratory epithelial cells

OBJECTIVE

Respiratory epithelial cells are the first natural barrier against bacteria and viruses; hence, the interactions among epithelial cells, bacteria, and viruses are associated with disease occurrence and development. The effect of co-infection by P. gingivalis and influenza A virus (IAV) on respiratory epithelial cells remains unknown. The aim of this study was to analyze in vitro cell viability and apoptosis rates in respiratory epithelial A549 cells infected with P. gingivalis or IAV alone, or a combination of both pathogens.

DESIGN

A549 cells were first divided into a control group, a P. gingivalis group, an IAV group, and a P. gingivalis + IAV group, to examine cell viability and apoptosis rates, the levels of microtubule associated protein 1 light chain 3 B (LC3-II), microtubule associated protein 1 light chain 3A (LC3-I), and sequestosome 1 (P62), and the formation of autophagosomes. The autophagy inhibitor, 3-methyladenine (3MA), was used to assess autophagy and apoptosis in A549 cells infected with P. gingivalis or IAV.

RESULTS

An MTT assay revealed that cell viability was significantly lower in the IAV group than in the P. gingivalis + IAV group (P < 0.05). Flow cytometry indicated that the apoptosis rate was significantly higher in the IAV group than in the P. gingivalis + IAV group (P < 0.05). The fluorescence levels of GFP-LC3 increased significantly, the LC3-II/LC3-I ratio was significantly higher, and the P62 protein levels were statistically lower in the P. gingivalis + IAV group compared with the IAV group (all P < 0.05). Western blotting revealed that the LC3- II/LC3-I ratio was significantly lower, and caspase-3 levels were significantly higher in the 3MA + P. gingivalis + IAV group compared to the P. gingivalis + IAV group (all P < 0.05).

CONCLUSION

In vitro studies showed that infection by P. gingivalis combined with IAV temporarily inhibited apoptosis in respiratory epithelial cells, and this may be related to the initiation of autophagy.

Quantifying the influence of temperature on hand, foot and mouth disease incidence in Wuhan, Central China

Hand, foot and mouth disease (HFMD) is a substantial burden throughout Asia, but the effects of temperature pattern on HFMD risk are inconsistent. To quantify the effect of temperature on HFMD incidence, Wuhan was chosen as the study site because of its high temperature variability and high HFMD incidence. Daily series of HFMD counts and meteorological variables during 2010-2015 were obtained. Distributed lag non-linear models were applied to characterize the temperature-HFMD relationship and to assess its variability across different ages, genders, and types of child care. Totally, 80,219 patients of 0-5 years experienced HFMD in 2010-2015 in Wuhan. The cumulative relative risk of HFMD increased linearly with temperature over 7 days (lag0-7), while it presented as an approximately inverted V-shape over 14 days (lag0-14). The cumulative relative risk at lag0-14 peaked at 26.4 °C with value of 2.78 (95%CI: 2.08-3.72) compared with the 5^th percentile temperature (1.7 °C). Subgroup analyses revealed that children attended daycare were more vulnerable to temperature variation than those cared for at home. This study suggests that public health actions should take into consideration local weather conditions and demographic characteristics.

Spatiotemporal risk mapping of hand, foot and mouth disease and its association with meteorological variables in children under 5 years

Hand, foot and mouth disease (HFMD) risk has become an increasing concern in the Beijing–Tianjin–Hebei region, which is the biggest urban agglomeration in north-eastern Asia. In the study, spatiotemporal epidemiological features of HFMD were analysed, and a Bayesian space–time hierarchy model was used to detect local spatial relative risk (RR) and to assess the effect of meteorological factors. From 2009 to 2013, there was an obvious seasonal pattern of HFMD risk. The highest risk period was in the summer, with an average monthly incidence of 4·17/103, whereas the index in wintertime was 0·16/103. Meteorological variables influenced temporal changes in HFMD. A 1 °C rise in air temperature was associated with an 11·5% increase in HFMD (corresponding RR 1·122). A 1% rise in relative humidity was related to a 9·51% increase in the number of HFMD cases (corresponding RR 1·100). A 1 hPa increment in air pressure was related to a 0·11% decrease in HFMD (corresponding RR 0·999). A 1 h increase in sunshine was associated with a 0·28% rise in HFMD cases (corresponding RR 1·003). A 1 m/s rise in wind speed was related to a 6·2% increase in HFMD (corresponding RR 1·064). High-risk areas were mainly large cities, such as Beijing, Tianjin, Shijiazhuang and their neighbouring areas. These findings can contribute to risk control and implementation of disease-prevention policies.

Development of Disease-specific, Context-specific Surveillance Models: Avian Influenza (H5N1)-Related Risks and Behaviours in African Countries

Avian influenza virus (H5N1) is a rapidly disseminating infection that affects poultry and, potentially, humans. Because the avian virus has already adapted to several mammalian species, decreasing the rate of avian-mammalian contacts is critical to diminish the chances of a total adaptation of H5N1 to humans. To prevent the pandemic such adaptation could facilitate, a biology-specific disease surveillance model is needed, which should also consider geographical and socio-cultural factors. Here, we conceptualized a surveillance model meant to capture H5N1-related biological and cultural aspects, which included food processing, trade and cooking-related practices, as well as incentives (or disincentives) for desirable behaviours. This proof of concept was tested with data collected from 378 Egyptian and Nigerian sites (local [backyard] producers/live bird markets/village abattoirs/commercial abattoirs and veterinary agencies). Findings revealed numerous opportunities for pathogens to disseminate, as well as lack of incentives to adopt preventive measures, and factors that promoted epidemic dissemination. Supporting such observations, the estimated risk for H5N1-related human mortality was higher than previously reported. The need for multidimensional disease surveillance models, which may detect risks at higher levels than models that only measure one factor or outcome, was supported. To develop efficient surveillance systems, interactions should be captured, which include but exceed biological factors. This low-cost and easily implementable model, if conducted over time, may identify focal instances where tailored policies may diminish both endemicity and the total adaptation of H5N1 to the human species.

The effect of meteorological variables on the transmission of hand, foot and mouth disease in four major cities of shanxi province, China: a time series data analysis (2009-2013)

Increased incidence of hand, foot and mouth disease (HFMD) has been recognized as a critical challenge to communicable disease control and public health response. This study aimed to quantify the association between climate variation and notified cases of HFMD in selected cities of Shanxi Province, and to provide evidence for disease control and prevention. Meteorological variables and HFMD cases data in 4 major cities (Datong, Taiyuan, Changzhi and Yuncheng) of Shanxi province, China, were obtained from the China Meteorology Administration and China CDC respectively over the period 1 January 2009 to 31 December 2013. Correlations analyses and Seasonal Autoregressive Integrated Moving Average (SARIMA) models were used to identify and quantify the relationship between the meteorological variables and HFMD. HFMD incidence varied seasonally with the majority of cases in the 4 cities occurring from May to July. Temperatures could play important roles in the incidence of HFMD in these regions. The SARIMA models indicate that a 1° C rise in average, maximum and minimum temperatures may lead to a similar relative increase in the number of cases in the 4 cities. The lag times for the effects of temperatures were identified in Taiyuan, Changzhi and Yuncheng. The numbers of cases were positively associated with average and minimum temperatures at a lag of 1 week in Taiyuan, Changzhi and Yuncheng, and with maximum temperature at a lag of 2 weeks in Yuncheng. Positive association between the temperature and HFMD has been identified from the 4 cities in Shanxi Province, although the role of weather variables on the transmission of HFMD varied in the 4 cities. Relevant prevention measures and public health action are required to reduce future risks of climate change with consideration of local climatic conditions.

Understanding of the impact of weather variables on HFMD transmission remains limited due to various local climatic conditions, socioeconomic status and demographic characteristics in different regions. This study provides quantitative evidence that the incidence of HFMD cases was significantly associated with temperature in Shanxi Province, North China. The delayed effects of weather variables on HFMD dictate different public health responses in 4 major cities in Shanxi Province. The results may provide a direction for local community and health authorities to perform public health actions, and the SARIMA models are helpful in the prediction of epidemics, determination of high-risk areas and susceptible populations, allocation of health resources, and the formulation of relevant prevention strategies. In order to reduce future risks of climatic variations on HFMD epidemics, similar studies in other geographical areas are needed, together with a longer study period to enable trend analysis which takes into consideration local weather conditions and demographic characteristics.