Changing Geographic Patterns and Risk Factors for Avian Influenza A(H7N9) Infections in Humans, China

Application of peripheral blood routine parameters in the diagnosis of influenza and Mycoplasma pneumoniae

OBJECTIVES

Influenza and Mycoplasma pneumoniae infections often present concurrent and overlapping symptoms in clinical manifestations, making it crucial to accurately differentiate between the two in clinical practice. Therefore, this study aims to explore the potential of using peripheral blood routine parameters to effectively distinguish between influenza and Mycoplasma pneumoniae infections.

METHODS

This study selected 209 influenza patients (IV group) and 214 Mycoplasma pneumoniae patients (MP group) from September 2023 to January 2024 at Nansha Division, the First Affiliated Hospital of Sun Yat-sen University. We conducted a routine blood-related index test on all research subjects to develop a diagnostic model. For normally distributed parameters, we used the T-test, and for non-normally distributed parameters, we used the Wilcoxon test.

RESULTS

Based on an area under the curve (AUC) threshold of ≥ 0.7, we selected indices such as Lym# (lymphocyte count), Eos# (eosinophil percentage), Mon% (monocyte percentage), PLT (platelet count), HFC# (high fluorescent cell count), and PLR (platelet to lymphocyte ratio) to construct the model. Based on these indicators, we constructed a diagnostic algorithm named IV@MP using the random forest method.

CONCLUSIONS

The diagnostic algorithm demonstrated excellent diagnostic performance and was validated in a new population, with an AUC of 0.845. In addition, we developed a web tool to facilitate the diagnosis of influenza and Mycoplasma pneumoniae infections. The results of this study provide an effective tool for clinical practice, enabling physicians to accurately diagnose and differentiate between influenza and Mycoplasma pneumoniae infection, thereby offering patients more precise treatment plans.

Effect of avian influenza scare on transmission of zoonotic avian influenza: A case study of influenza A (H7N9)

Avian influenza scare is a human psychological factor that asserts both positive and negative effects on the transmission of zoonotic avian influenza. In order to study the dichotomous effect of avian influenza scare on disease transmission, taking H7N9 avian influenza as a typical case, a two-patch epidemic model is proposed. The global dynamics and the threshold criteria are established by LaSalle invariant principle and the theory of asymptotic autonomous system. To mitigate the negative effects and curb illegal poultry trade, a game-theoretic model is adopted to explore the optimal policy of culling subsidies to reasonably compensate stakeholders for their economic losses resulting from the scare. The optimal policy of culling subsidy is found to heavily depend on the penalty of illegal poultry trade, the stakeholders' income, the intensity of control measures, and the prevalence level of the disease. The negative effect of avian influenza scare on disease transmission is considerably more significant than the positive effect. In order to avoid a widespread outbreak of zoonotic avian influenza across the region, a comprehensive national global control strategy is essential and effective, even in the presence of the negative effect of the avian influenza scare.

Enhanced environmental surveillance for avian influenza A/H5, H7 and H9 viruses in Guangxi, China, 2017-2019

We conducted environmental surveillance to detect avian influenza viruses circulating at live poultry markets (LPMs) and poultry farms in Guangxi Autonomous Region, China, where near the China-Vietnam border. From November through April 2017-2018 and 2018-2019, we collected environmental samples from 14 LPMs, 4 poultry farms, and 5 households with backyard poultry in two counties of Guangxi and tested for avian influenza A, H5, H7, and H9 by real-time reverse transcription-polymerase chain reaction (rRT-PCR). In addition, we conducted four cross-sectional questionnaire surveys among stall owners on biosecurity practices in LPMs of two study sites. Among 16,713 environmental specimens collected and tested, the median weekly positive rate for avian influenza A was 53.6% (range = 33.5% - 66.0%), including 25.2% for H9, 4.9% for H5, and 21.2% for other avian influenza viruses A subtypes, whereas a total of two H7 positive samples were detected. Among the 189 LPM stalls investigated, most stall owners (73.0%) sold chickens and ducks. Therefore, continued surveillance of the avian influenza virus is necessary for detecting and responding to emerging trends in avian influenza virus epidemiology.

Spatio-temporal spread and evolution of influenza A (H7N9) viruses

The influenza A (H7N9) virus has been seriously concerned for its potential to cause an influenza pandemic. To understand the spread and evolution process of the virus, a spatial and temporal Bayesian evolutionary analysis was conducted on 2,052 H7N9 viruses isolated during 2013 and 2018. It revealed that the H7N9 virus was probably emerged in a border area of Anhui Province in August 2012, approximately 6 months earlier than the first human case reported. Two major epicenters had been developed in the Yangtze River Delta and Peral River Delta regions by the end of 2013, and from where the viruses have also spread to other regions at an average speed of 6.57 km/d. At least 24 genotypes showing have been developed and each of them showed a distinct spatio-temporal distribution pattern. Furthermore, A random forest algorithm-based model has been developed to predict the occurrence risk of H7N9 virus. The model has a high overall forecasting precision (> 97%) and the monthly H7N9 occurrence risk for each county of China was predicted. These findings provide new insights for a comprehensive understanding of the origin, evolution, and occurrence risk of H7N9 virus. Moreover, our study also lays a theoretical basis for conducting risk-based surveillance and prevention of the disease.

Small-scale spatiotemporal epidemiology of notifiable infectious diseases in China: a systematic review

Background

The prevalence of infectious diseases remains one of the major challenges faced by the Chinese health sector. Policymakers have a tremendous interest in investigating the spatiotemporal epidemiology of infectious diseases. We aimed to review the small-scale (city level, county level, or below) spatiotemporal epidemiology of notifiable infectious diseases in China through a systematic review, thus summarizing the evidence to facilitate more effective prevention and control of the diseases.

Methods

We searched four English language databases (PubMed, EMBASE, Cochrane Library, and Web of Science) and three Chinese databases (CNKI, WanFang, and SinoMed), for studies published between January 1, 2004 (the year in which China’s Internet-based disease reporting system was established) and December 31, 2021. Eligible works were small-scale spatial or spatiotemporal studies focusing on at least one notifiable infectious disease, with the entire territory of mainland China as the study area. Two independent reviewers completed the review process based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

Results

A total of 18,195 articles were identified, with 71 eligible for inclusion, focusing on 22 diseases. Thirty-one studies (43.66%) were analyzed using city-level data, 34 (47.89%) were analyzed using county-level data, and six (8.45%) used community or individual data. Approximately four-fifths (80.28%) of the studies visualized incidence using rate maps. Of these, 76.06% employed various spatial clustering methods to explore the spatial variations in the burden, with Moran’s I statistic being the most common. Of the studies, 40.85% explored risk factors, in which the geographically weighted regression model was the most commonly used method. Climate, socioeconomic factors, and population density were the three most considered factors.

Conclusions

Small-scale spatiotemporal epidemiology has been applied in studies on notifiable infectious diseases in China, involving spatiotemporal distribution and risk factors. Health authorities should improve prevention strategies and clarify the direction of future work in the field of infectious disease research in China.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07669-9.

Assessment of the spatiotemporal risk of avian influenza between waterfowl and poultry farms during the annual cycle: A spatial prediction study focused on seasonal distribution changes in resident waterfowl in South Korea

Previous studies and efforts to prevent and manage avian influenza (AI) outbreaks have mainly focused on the wintering season. However, outbreaks of AI have been reported in the summer, including the breeding season of waterfowl. Additionally, the spatial distribution of waterfowl can easily change during the annual cycle due to their life-cycle traits and the presence of both migrants and residents in the population. Thus, we assessed the spatiotemporal variation in AI exposure risk in poultry due to spatial distribution changes in three duck species included in both major residents and wintering migrants in South Korea, the mandarin, mallard and spot-billed duck, during wintering (October-March), breeding (April-June) and whole annual seasons. To estimate seasonal ecological niche variations among the three duck species, we applied pairwise ecological niche analysis using the Pianka index. Subsequently, seasonal distribution models were projected by overlaying the monthly ranges estimated by the maximum entropy model. Finally, we overlaid each seasonal distribution range onto a poultry distribution map of South Korea. We found that the mandarin had less niche overlap with the mallard and spot-billed duck during the wintering season than during the breeding season, whereas the mallard had less niche overlap with the mandarin and spot-billed duck during the breeding season than during the wintering season. Breeding and annual distribution ranges of the mandarin and spot-billed duck, but not the mallard, were similar or even wider than their wintering ranges. Similarly, the mandarin and spot-billed duck showed more extensive overlap proportions between poultry and their distributional ranges during both the breeding and annual seasons than during the wintering season. These results suggest that potential AI exposure in poultry can occur more widely in the summer than in winter, depending on sympatry with the host duck species. Future studies considering the population density and variable pathogenicity of AI are required.

Spatial Variation in Risk for Highly Pathogenic Avian Influenza Subtype H5N6 Viral Infections in South Korea: Poultry Population-Based Case–Control Study

Given the substantial economic damage caused by the continual circulation of highly pathogenic avian influenza (HPAI) outbreaks since 2003, identifying high-risk locations associated with HPAI infections is essential. In this study, using affected and unaffected poultry farms’ locations during an HPAI H5N6 epidemic in South Korea, we identified places where clusters of HPAI cases were found. Hotspots were defined as regions having clusters of HPAI cases. With the help of the statistical computer program R, a kernel density estimate and a spatial scan statistic were employed for this purpose. A kernel density estimate and detection of significant clusters through a spatial scan statistic both showed that districts in the Chungcheongbuk-do, Jeollabuk-do, and Jeollanam-do provinces are more vulnerable to HPAI outbreaks. Prior to the migration season, high-risk districts should implement particular biosecurity measures. High biosecurity measures, as well as improving the cleanliness of the poultry environment, would undoubtedly aid in the prevention of HPAIV transmission to poultry farms in these high-risk regions of South Korea.

Transmission dynamics and optimal control of H7N9 in China

H7N9 avian influenza is a highly pathogenic zoonotic disease. In order to control the disease, many strategies have been adopted in China such as poultry culling, the closure of live poultry markets (LPMs), the vaccination of poultry, and the treatment for humans. Due to the limited resource, it is of paramount significance to achieve the optimal control. In this paper, an epidemic model incorporating the selective culling rate is formulated to investigate the transmission mechanism of H7N9. The threshold dynamics and bifurcation analyses of the model are well investigated. Furthermore, the problem of optimal control is explored in line with Pontryagin’s Maximum Principle, with consideration given to the comprehensive measures. The numerical simulations suggest that the vaccination of poultry and the closure of LPMs are the two most economical and effective measures.

Two-stage algorithms for visually exploring spatio-temporal clustering of avian influenza virus outbreaks in poultry farms

The development of visual tools for the timely identification of spatio-temporal clusters will assist in implementing control measures to prevent further damage. From January 2015 to June 2020, a total number of 1463 avian influenza outbreak farms were detected in Taiwan and further confirmed to be affected by highly pathogenic avian influenza subtype H5Nx. In this study, we adopted two common concepts of spatio-temporal clustering methods, the Knox test and scan statistics, with visual tools to explore the dynamic changes of clustering patterns. Since most (68.6%) of the outbreak farms were detected in 2015, only the data from 2015 was used in this study. The first two-stage algorithm performs the Knox test, which established a threshold of 7 days and identified 11 major clusters in the six counties of southwestern Taiwan, followed by the standard deviational ellipse (SDE) method implemented on each cluster to reveal the transmission direction. The second algorithm applies scan likelihood ratio statistics followed by AGC index to visualize the dynamic changes of the local aggregation pattern of disease clusters at the regional level. Compared to the one-stage aggregation approach, Knox-based and AGC mapping were more sensitive in small-scale spatio-temporal clustering.

Analysis of the movement of live broilers in Guangxi, China and implications for avian influenza control

Most Chinese provinces have a daily-updated database of live animal movements; however, the data are not efficiently utilized to support interventions to control H7N9 and other avian influenzas. Based on official records, this study assessed the spatio-temporal patterns of live broilers moved out of and within Guangxi in 2017. The yearly and monthly networks were analyzed for inter- and intra-provincial movements, respectively. Approximately 200,000 movements occurred in 2017, involving the transport of 200 million live broilers from Guangxi. Although Guangxi exported to 24 out of 32 provinces of China, 95% of inter-provincial movements occurred with three bordering provinces. Within Guangxi, counties were highly connected through the live broiler movements, creating conditions for rapid virus spreading throughout the province. Interestingly, a peak in movements during the Chinese Lunar New Year celebrations, late January in 2017, was not observed in this study, likely due to H7N9-related control measures constraining live bird trading. Both intra- and inter-provincial movements in March 2017 were significantly higher than in other months of that year, suggesting that dramatic price changes may influence the movement's network and reshape the risk pathways. However, despite these variations, the same small proportion of counties (less than 20%) exporting/importing more than 90% of inter- and intra-provincial movements remains the same throughout the year. Interventions, particularly surveillance and improving biosecurity, targeted to those counties are thus likely to be more effective for avian influenza risk mitigation than implemented indiscriminately. Additionally, simulations further demonstrated that targeting counties according to their degree or betweenness in the movement network would be the most efficient way to limit disease transmission via broiler movements. The study findings provide evidence to support the design of risk-based control interventions for H7N9 and all other avian influenza viruses in broiler value chains in Guangxi.

Spatio-temporal Differentiation in the Incidence of Influenza and Its Relationship with Air Pollution in China from 2004 to 2017

The Healthy China Initiative is a major health strategy being pursued by the country. To prevent and control different types of diseases as well as their complex variants, research on the spatio-temporal differentiation among and mechanisms of influence of epidemic diseases is growing worldwide. This study analyzed monthly data on the incidence of influenza by using different methods, including Moran's I, the hotspot analysis model, concentration analysis, and correlation analysis, to determine the characteristics of spatio-temporal differentiation in the incidence of influenza across prefecture-level cities in China from 2004 to 2017, and to examine its relationship with air pollution. According to the results, the overall incidence of influenza in China exhibited a trend of increase from 2004 to 2017, with small peaks in 2009 and 2014. More cases of influenza were recorded in the first and fourth quarters of each year. Regions with higher incidences of influenza were concentrated in northwestern and northern China, and in the coastal areas of southeastern China. Over time, the distribution of regions with a higher incidence of influenza has shifted from the west to the east of the country. A significant relationship was observed between the incidence of influenza and factors related to air pollution. The contents of five air pollutants (PM2.5, PM10, SO2, NO2, and CO) were significantly positively correlated with the incidence of influenza, with a decreasing order of contribution to it of SO2 > CO > NO2 > PM2.5 > PM10. The content of O3 in the air was negatively correlated with the incidence of influenza. The influence of air pollution-related factors on the incidence of influenza in different regions and seasons showed minor differences. The large-scale empirical results provided here can supply a scientific basis for governmental disease control authorities to formulate strategies for regional prevention and control.

Geospatial modelling to estimate the territory at risk of establishment of influenza type A in Mexico - An ecological study

The aim of this study was to estimate the territory at risk of establishment of influenza type A (EOITA) in Mexico, using geospatial models. A spatial database of 1973 outbreaks of influenza worldwide was used to develop risk models accounting for natural (natural threat), anthropic (man-made) and environmental (combination of the above) transmission. Then, a virus establishment risk model; an introduction model of influenza A developed in another study; and the three models mentioned were utilized using multi-criteria spatial evaluation supported by geographically weighted regression (GWR), receiver operating characteristic analysis and Moran's I. The results show that environmental risk was concentrated along the Gulf and Pacific coasts, the Yucatan Peninsula and southern Baja California. The identified risk for EOITA in Mexico were: 15.6% and 4.8%, by natural and anthropic risk, respectively, while 18.5% presented simultaneous environmental, natural and anthropic risk. Overall, 28.1% of localities in Mexico presented a High/High risk for the establishment of influenza type A (area under the curve=0.923, P<0.001; GWR, r2=0.840, P<0.001; Moran's I =0.79, P<0.001). Hence, these geospatial models were able to robustly estimate those areas susceptible to EOITA, where the results obtained show the relation between the geographical area and the different effects on health. The information obtained should help devising and directing strategies leading to efficient prevention and sound administration of both human and financial resources.

A framework for the risk prediction of avian influenza occurrence: An Indonesian case study

Avian influenza viruses can cause economically devastating diseases in poultry and have the potential for zoonotic transmission. To mitigate the consequences of avian influenza, disease prediction systems have become increasingly important. In this study, we have proposed a framework for the prediction of the occurrence and spread of avian influenza events in a geographical area. The application of the proposed framework was examined in an Indonesian case study. An extensive list of historical data sources containing disease predictors and target variables was used to build spatiotemporal and transactional datasets. To combine disparate sources, data rows were scaled to a temporal scale of 1-week and a spatial scale of 1-degree × 1-degree cells. Given the constructed datasets, underlying patterns in the form of rules explaining the risk of occurrence and spread of avian influenza were discovered. The created rules were combined and ordered based on their importance and then stored in a knowledge base. The results suggested that the proposed framework could act as a tool to gain a broad understanding of the drivers of avian influenza epidemics and may facilitate the prediction of future disease events.

Ecological factors associated with persistent circulation of multiple highly pathogenic avian influenza viruses among poultry farms in Taiwan during 2015-17

Emergence and intercontinental spread of highly pathogenic avian influenza A (HPAI) H5Nx virus clade 2.3.4.4 has resulted in substantial economic losses to the poultry industry in Asia, Europe, and North America. The long-distance migratory birds have been suggested to play a major role in the global spread of avian influenza viruses during this wave of panzootic outbreaks since 2013. Poultry farm epidemics caused by multiple introduction of different HPAI novel subtypes of clade 2.3.4.4 viruses also occurred in Taiwan between 2015 and 2017. The mandatory and active surveillance detected H5N3 and H5N6 circulation in 2015 and 2017, respectively, while H5N2 and H5N8 were persistently identified in poultry farms since their first arrival in 2015. This study intended to assess the importance of various ecological factors contributed to the persistence of HPAI during three consecutive years. We used satellite technology to identify the location of waterfowl flocks. Four risk factors consistently showed strong association with the spatial clustering of H5N2 and H5N8 circulations during 2015 and 2017, including high poultry farm density (aOR:17.46, 95%CI: 5.91–74.86 and 8.23, 95% CI: 2.12–54.86 in 2015 and 2017, respectively), poultry heterogeneity index (aOR of 12.28, 95%CI: 5.02–31.14 and 2.79, 95%CI: 1.00–7.69, in 2015 and 2017, respectively), non-registered waterfowl flock density (aOR: 6.8, 95%CI: 3.41–14.46 and 9.17, 95%CI: 3.73–26.20, in 2015 and 2017, respectively) and higher percentage of cropping land coverage (aOR of 1.36, 95%CI: 1.10–1.69 and 1.04, 95%CI: 1.02–1.07, in 2015 and 2017, respectively). Our study highlights the application of remote sensing and clustering analysis for the identification and characterization of environmental factors in facilitating and contributing to the persistent circulation of certain subtypes of H5Nx in poultry farms in Taiwan.

Geographical variation in the risk of H7N9 human infections in China: implications for risk-based surveillance

The influenza A (H7N9) subtype remains a public health problem in China affecting individuals in contact with live poultry, particularly at live bird markets. Despite enhanced surveillance and biosecurity at LBMs H7N9 viruses are now more widespread in China. This study aims to quantify the temporal relationship between poultry surveillance results and the onset of human H7N9 infections during 2013-2017 and to estimate risk factors associated with geographical risk of H7N9 human infections in counties in Southeast China. Our results suggest that poultry surveillance data can potentially be used as early warning indicators for human H7N9 notifications. Furthermore, we found that human H7N9 incidence at county-level was significantly associated with the presence of wholesale LBMs, the density of retail LBMs, the presence of poultry virological positives, poultry movements from high-risk areas, as well as chicken population density and human population density. The results of this study can influence the current AI H7N9 control program by supporting the integration of poultry surveillance data with human H7N9 notifications as an early warning of the timing and areas at risk for human infection. The findings also highlight areas in China where monitoring of poultry movement and poultry infections could be prioritized.

Live poultry market closure and avian influenza A (H7N9) infection in cities of China, 2013-2017: an ecological study

Background

Previous studies have proven that the closure of live poultry markets (LPMs) was an effective intervention to reduce human risk of avian influenza A (H7N9) infection, but evidence is limited on the impact of scale and duration of LPMs closure on the transmission of H7N9.

Method

Five cities (i.e., Shanghai, Suzhou, Shenzhen, Guangzhou and Hangzhou) with the largest number of H7N9 cases in mainland China from 2013 to 2017 were selected in this study. Data on laboratory-confirmed H7N9 human cases in those five cities were obtained from the Chinese National Influenza Centre. The detailed information of LPMs closure (i.e., area and duration) was obtained from the Ministry of Agriculture. We used a generalized linear model with a Poisson link to estimate the effect of LPMs closure, reported as relative risk reduction (RRR). We used classification and regression trees (CARTs) model to select and quantify the dominant factor of H7N9 infection.

Results

All five cities implemented the LPMs closure, and the risk of H7N9 infection decreased significantly after LPMs closure with RRR ranging from 0.80 to 0.93. Respectively, a long-term LPMs closure for 10–13 weeks elicited a sustained and highly significant risk reduction of H7N9 infection (RRR = 0.98). Short-time LPMs closure with 2 weeks in every epidemic did not reduce the risk of H7N9 infection (p > 0.05). Partially closed LPMs in some suburbs contributed only 35% for reduction rate (RRR = 0.35). Shenzhen implemented partial closure for first 3 epidemics (p > 0.05) and all closure in the latest 2 epidemic waves (RRR = 0.64).

Conclusion

Our findings suggest that LPMs all closure in whole city can be a highly effective measure comparing with partial closure (i.e. only urban closure, suburb and rural remain open). Extend the duration of closure and consider permanently closing the LPMs will help improve the control effect. The effect of LPMs closure seems greater than that of meteorology on H7N9 transmission.

Effectiveness of Live Poultry Market Interventions on Human Infection with Avian Influenza A(H7N9) Virus, China

Various interventions for live poultry markets (LPMs) have emerged to control outbreaks of avian influenza A(H7N9) virus in mainland China since March 2013. We assessed the effectiveness of various LPM interventions in reducing transmission of H7N9 virus across 5 annual waves during 2013-2018, especially in the final wave. With the exception of waves 1 and 4, various LPM interventions reduced daily incidence rates significantly across waves. Four LPM interventions led to a mean reduction of 34%-98% in the daily number of infections in wave 5. Of these, permanent closure provided the most effective reduction in human infection with H7N9 virus, followed by long-period, short-period, and recursive closures in wave 5. The effectiveness of various LPM interventions changed with the type of intervention across epidemics. Permanent LPM closure should be considered to maintain sufficient effectiveness of interventions and prevent the recurrence of H7N9 epidemics.

A brief history of bird flu

In 1918, a strain of influenza A virus caused a human pandemic resulting in the deaths of 50 million people. A century later, with the advent of sequencing technology and corresponding phylogenetic methods, we know much more about the origins, evolution and epidemiology of influenza epidemics. Here we review the history of avian influenza viruses through the lens of their genetic makeup: from their relationship to human pandemic viruses, starting with the 1918 H1N1 strain, through to the highly pathogenic epidemics in birds and zoonoses up to 2018. We describe the genesis of novel influenza A virus strains by reassortment and evolution in wild and domestic bird populations, as well as the role of wild bird migration in their long-range spread. The emergence of highly pathogenic avian influenza viruses, and the zoonotic incursions of avian H5 and H7 viruses into humans over the last couple of decades are also described. The threat of a new avian influenza virus causing a human pandemic is still present today, although control in domestic avian populations can minimize the risk to human health.

This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’. This issue is linked with the subsequent theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’.

Different nasopharynx and oropharynx microbiota imbalance in children with Mycoplasma pneumoniae or influenza virus infection

BACKGROUND

The Mycoplasma pneumoniae(MP) and influenza virus are two common pathogens causing pediatric acute respiratory tract infection. Though emerging reports demonstrated imbalanced respiratory microbiota in respiratory infection, the respiratory microbiota differences between MP and influenza virus remained to be explored.

METHODS

We collected paired nasopharyngeal(NP) and oropharyngeal(OP) microbial samples from 165 children, including 40 patients with MP pneumonia, 66 patients with influenza virus infection and 59 age-matched healthy children.

RESULTS

The NP and OP microbial diversity decreased in MP infection and increased in influenza infection as compared to healthy children. The Staphylococcus dominated Mycoplasma pneumoniae pneumonia(MPP) patients' NP microbiota while five representative patterns remained in influenza patients. In OP microbiota, Streptococcus significantly enriched in MPP group and decreased in Influenza group. Decision tree analysis indicated that Ralstonia and Acidobacteria could discriminate microbial samples in healthy (59/67), MP (35/38) and Influenza groups (55/60) with high accuracy.

CONCLUSIONS

This study revealed that dominant bacterial structure in the airway was niche- and disease-specific. It could facilitate the stratification of respiratory microbial samples with different infectious agents.

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.

Characterization of H7N9 avian influenza viruses isolated from duck meat products

Avian influenza H7N9 viruses have caused five epidemic waves of human infections since the first human cases were reported in 2013. In 2016, the initial low pathogenic avian influenza (LPAI) H7N9 viruses became highly pathogenic, acquiring multi-basic amino acids at the haemagglutinin cleavage site. These highly pathogenic avian influenza (HPAI) H7N9 viruses have been detected in poultry and humans in China, causing concerns of a serious threat to global public health. In Japan, both HPAI and LPAI H7N9 viruses were isolated from duck meat products carried illegally and relinquished voluntarily at the border by passengers on flights from China to Japan between 2016 and 2017. Some of the LPAI and HPAI H7N9 viruses detected at the border in Japan were characterized previously in chickens and ducks; however, their pathogenicity and replicative ability in mammals remain unknown. In this study, we assessed the biological features of two HPAI H7N9 virus isolates [A/duck/Japan/AQ-HE29-22/2017 (HE29-22) and A/duck/Japan/AQ-HE29-52/2017 (HE29-52); both of these viruses were isolated from duck meat at the border)] and an LPAI H7N9 virus isolate [A/duck/Japan/AQ-HE28-3/2016 (HE28-3)] in mice and ferrets. In mice, HE29-52 was more pathogenic than HE29-22 and HE28-3. In ferrets, the two HPAI virus isolates replicated more efficiently in the lower respiratory tract of the animals than did the LPAI virus isolate. Our results indicate that HPAI H7N9 viruses with the potential to cause severe diseases in mammals have been illegally introduced to Japan.

Malaria risk assessment and mapping using satellite imagery and boosted regression trees in the Peruvian Amazon

This is the first study to assess the risk of co-endemic Plasmodium vivax and Plasmodium falciparum transmission in the Peruvian Amazon using boosted regression tree (BRT) models based on social and environmental predictors derived from satellite imagery and data. Yearly cross-validated BRT models were created to discriminate high-risk (annual parasite index API > 10 cases/1000 people) and very-high-risk for malaria (API > 50 cases/1000 people) in 2766 georeferenced villages of Loreto department, between 2010-2017 as other parts in the article (graphs, tables, and texts). Predictors were cumulative annual rainfall, forest coverage, annual forest loss, annual mean land surface temperature, normalized difference vegetation index (NDVI), normalized difference water index (NDWI), shortest distance to rivers, time to populated villages, and population density. BRT models built with predictor data of a given year efficiently discriminated the malaria risk for that year in villages (area under the ROC curve (AUC) > 0.80), and most models also effectively predicted malaria risk in the following year. Cumulative rainfall, population density and time to populated villages were consistently the top three predictors for both P. vivax and P. falciparum incidence. Maps created using the BRT models characterize the spatial distribution of the malaria incidence in Loreto and should contribute to malaria-related decision making in the area.

Sequential Immunization with Universal Live Attenuated Influenza Vaccine Candidates Protects Ferrets against a High-Dose Heterologous Virus Challenge

The development of universal influenza vaccines has been a priority for more than 20 years. We conducted a preclinical study in ferrets of two sets of live attenuated influenza vaccines (LAIVs) expressing chimeric hemagglutinin (cHA). These vaccines contained the HA stalk domain from H1N1pdm09 virus but had antigenically unrelated globular head domains from avian influenza viruses H5N1, H8N4 and H9N2. The viral nucleoproteins (NPs) in the two sets of universal LAIV candidates were from different sources: one LAIV set contained NP from A/Leningrad/17 master donor virus (MDV), while in the other set this gene was from wild-type (WT) H1N1pdm09 virus, in order to better match the CD8 T-cell epitopes of currently circulating influenza A viruses. To avoid any difference in protective effect of the various anti-neuraminidase (NA) antibodies, all LAIVs were engineered to contain the NA gene of Len/17 MDV. Naïve ferrets were sequentially immunized with three doses of (i) classical LAIVs containing non-chimeric HA and NP from MDV (LAIVs (NP-MDV)); (ii) cHA-based LAIVs containing NP from MDV (cHA LAIVs (NP-MDV)); and (iii) cHA-based LAIVs containing NP from H1N1pdm09 virus (cHA LAIVs (NP-WT)). All vaccination regimens were safe, producing no significant increase in body temperature or weight loss, in comparison with the placebo group. The two groups of cHA-based vaccines induced a broadly reactive HA stalk-directed antibody, while classical LAIVs did not. A high-dose challenge with H1N1pdm09 virus induced significant pathology in the control, non-immunized ferrets, including high virus titers in respiratory tissues, clinical signs of disease and histopathological changes in nasal turbinates and lung tissues. All three vaccination regimens protected animals from clinical manifestations of disease: immunized ferrets did not lose weight or show clinical symptoms, and their fever was significantly lower than in the control group. Further analysis of virological and pathological data revealed the following hierarchy in the cross-protective efficacy of the vaccines: cHA LAIVs (NP-WT) > cHA LAIVs (NP-MDV) > LAIVs (NP-MDV). This ferret study showed that prototype universal cHA-based LAIVs are highly promising candidates for further clinical development.

Molecular Evolution, Diversity, and Adaptation of Influenza A(H7N9) Viruses in China

The substantial increase in prevalence and emergence of antigenically divergent or highly pathogenic influenza A(H7N9) viruses during 2016–17 raises concerns about the epizootic potential of these viruses. We investigated the evolution and adaptation of H7N9 viruses by analyzing available data and newly generated virus sequences isolated in Guangdong Province, China, during 2015–2017. Phylogenetic analyses showed that circulating H7N9 viruses belong to distinct lineages with differing spatial distributions. Hemagglutination inhibition assays performed on serum samples from patients infected with these viruses identified 3 antigenic clusters for 16 strains of different virus lineages. We used ancestral sequence reconstruction to identify parallel amino acid changes on multiple separate lineages. We inferred that mutations in hemagglutinin occur primarily at sites involved in receptor recognition or antigenicity. Our results indicate that highly pathogenic strains likely emerged from viruses circulating in eastern Guangdong Province during March 2016 and are associated with a high rate of adaptive molecular evolution.

The epidemic potential of avian influenza A (H7N9) virus in humans in mainland China: A two-stage risk analysis

Background

From 2013 to 2017, more than one thousand avian influenza A (H7N9) confirmed cases with hundreds of deaths were reported in mainland China. To identify priorities for epidemic prevention and control, a risk assessing framework for subnational variations is needed to define the epidemic potential of A (H7N9).

Methods

We established a consolidated two-stage framework that outlined the potential epidemic of H7N9 in humans: The Stage 1, index-case potential, used a Boosted Regression Trees model to assess population at risk due to spillover from poultry; the Stage 2, epidemic potential, synthesized the variables upon a framework of the Index for Risk Management to measure epidemic potential based on the probability of hazards and exposure, the vulnerability and coping capacity.

Results

Provinces in southern and eastern China, especially Jiangsu, Zhejiang, Guangzhou, have high index-case potential of human infected with A (H7N9), while northern coastal provinces and municipalities with low morbidity, i.e. Tianjin and Liaoning, have an increasing risk of A (H7N9) infection. Provinces in central China are likely to have high potential of epidemic due to the high vulnerability and the lack of coping capacity.

Conclusions

This study provides a unified risk assessment of A (H7N9) to detect the two-stage heterogeneity of epidemic potential among different provinces in mainland China, allowing proactively evaluate health preparedness at subnational levels to improve surveillance, diagnostic capabilities, and health promotion.

On the predictability of infectious disease outbreaks

Infectious disease outbreaks recapitulate biology: they emerge from the multi-level interaction of hosts, pathogens, and environment. Therefore, outbreak forecasting requires an integrative approach to modeling. While specific components of outbreaks are predictable, it remains unclear whether fundamental limits to outbreak prediction exist. Here, adopting permutation entropy as a model independent measure of predictability, we study the predictability of a diverse collection of outbreaks and identify a fundamental entropy barrier for disease time series forecasting. However, this barrier is often beyond the time scale of single outbreaks, implying prediction is likely to succeed. We show that forecast horizons vary by disease and that both shifting model structures and social network heterogeneity are likely mechanisms for differences in predictability. Our results highlight the importance of embracing dynamic modeling approaches, suggest challenges for performing model selection across long time series, and may relate more broadly to the predictability of complex adaptive systems.

Spatiotemporal Variation and Hotspot Detection of the Avian Influenza A(H7N9) Virus in China, 2013⁻2017

This study aims to describe the spatial and temporal characteristics of human infections with H7N9 virus in China using data from 19 February 2013 to 30 September 2017 extracted from Centre for Health Protection of the Department of Health (CHP) and electronic databases managed by China's Center for Disease Control (CDC) and provincial CDCs synthetically using the Geographic Information System (GIS) software ArcMap™ 10.2 and SaTScan. Based on the multiple analyses of the A(H7N9) epidemics, there was a strong seasonal pattern in A(H7N9) virus infection, with high activity in the first quarter of the year, especially in January, February, and April, and a gradual dying out in the third quarter. Spatial distribution analysis indicated that Eastern China contained the most severely affected areas, such as Zhejiang Province, and the distribution shifted from coastline areas to more inland areas over time. In addition, the cases exhibited local spatial aggregation, with high-risk areas most found in the southeast coastal regions of China. Shanghai, Jiangsu, Zhejiang, and Guangdong were the high-risk epidemic areas, which should arouse the attention of local governments. A strong cluster from 9 April 2017 to 24 June 2017 was also identified in Northern China, and there were many secondary clusters in Eastern and Southern China, especially in Zhejiang, Fujian, Jiangsu, and Guangdong Provinces. Our results suggested that the spatial-temporal clustering of H7N9 in China is fundamentally different, and is expected to contribute to accumulating knowledge on the changing temporal patterns and spatial dissemination during the fifth epidemic and provide data to enable adequate preparation against the next epidemic.

One health insights to prevent the next HxNy viral outbreak: learning from the epidemiology of H7N9

Background

With an increased incidence of viral zoonoses, there is an impetus to strengthen collaborations between public health, agricultural and environmental departments. This interdisciplinary cooperation, also known as the ‘One Health’ approach, has received significant support from various stakeholders. However, current efforts and policies still fall short of those needed for an effective One Health approach towards disease control and prevention. The avian-origin H7N9 influenza A virus outbreak in China serves as an ideal case study to emphasise this point.

Discussion

Here, we present the features and epidemiology of human infections with H7N9 influenza virus. At the early stages of the H7N9 epidemic, there was limited virus surveillance and limited prevention measures implemented in live poultry markets. As a result, zoonotic infections with H7N9 influenza viruses continued to enlarge in both numbers and geographic distribution. It was only after the number of human infections with H7N9 influenza virus spiked in the 5th wave of the epidemic that inter-departmental alliances were formed. This resulted in the rapid control of the number of human infections. We therefore further discuss the barriers that prevented the implementation of an effective One Health approach in China and what this means for other emerging, zoonotic viral diseases.

Summary

Effective implementation of evidence-based disease management approaches in China will result in substantial health and economic gains. The continual threat of avian influenza, as well as other emerging zoonotic viral infections, emphasizes the need to remove the barriers that prevent the effective implementation of One Health policies in disease management.

Spatiotemporal Distributions and Dynamics of Human Infections with the A H7N9 Avian Influenza Virus

In 2013 in mainland China, a novel avian influenza virus H7N9 began to infect humans and had aroused severe fatality in the infected humans, followed by the annual outbreaks. By methods of GIS and kriging interpolation, we get the geographical distributions. We obtain the longitudinal characteristics of these outbreaks based on statistics and diagrams. After these spatiotemporal distributions, an eco-epidemiological model is established and analyzed. In this model, the general incidence functions, the factor of fully killed infected poultry, and the virus in environment are taken into account. Theoretical analysis shows that the endemic will be formed to a large extent once the H7N9 avian influenza virus exists in poultry. On the basis of dynamics, we explore the possible disease control measures by numerical simulations. Simulations indicate that measures of vaccination in poultry and stopping live poultry transactions are the primary choices for disease control in humans, and strengthened inhibition effects and environmental disinfections can effectively control the outbreak.

Establishment of sandwich ELISA for detecting the H7 subtype influenza A virus

Avian H7N9 subtype influenza virus infects human with high case-fatality rate since it emerged in 2013. Although the vaccination has been rapidly used in poultry due to the emergence of highly pathogenic strain, this virus remains prevalent in this region. Thus, rapid diagnosis both in poultry and human clinic is critically important for the control and prevention of H7N9 infection. In this study, a batch of H7 subtype-specific monoclonal antibodies (mAbs) were developed and a pair of mAb, 2B6, and 5E9 were used to establish a double-antibody sandwich enzyme-linked immunosorbent assay (ELISA) to quantify H7 protein and detect influenza A virus baring H7 subtype HA. The lowest detection limit for the recombinant H7 protein was 10 ng/mL and 0.5 HAU/50 μL of A/Guangdong/17SF003/2016(H7N9), 2 HAU/50 μL of A/Netherlands/219/2003(H7N7) and A/Anhui/1/2013(H7N9) for live virus, respectively. The ELISA could not only detect the prevailing H7N9 virus, but also antigenic drift H7 subtype viruses, showing excellent sensitivity and high specificity. Hence, it could serve as a valuable approach to diagnose H7 subtype virus which showed great potential to cause pandemic, as well as antigen quantification.

Distinct Nasopharyngeal and Oropharyngeal Microbiota of Children with Influenza A Virus Compared with Healthy Children

BACKGROUND

Influenza A virus (IAV) has had the highest morbidity globally over the past decade. A growing number of studies indicate that the upper respiratory tract (URT) microbiota plays a key role for respiratory health and that a dysfunctional respiratory microbiota is associated with disease; but the impact of microbiota during influenza is understudied.

METHODS

We recruited 180 children, including 121 IAV patients and 59 age-matched healthy children. Nasopharyngeal (NP) and oropharyngeal (OP) swabs were collected to conduct 16S rDNA sequencing and compare microbiota structures in different individuals.

RESULTS

Both NP and OP microbiota in IAV patients differed from those in healthy individuals. The NP dominated genera in IVA patients, such as Moraxella, Staphylococcus, Corynebacterium, and Dolosigranulum, showed lower abundance than in healthy children. The Streptococcus significantly enriched in patients' NP and Phyllobacterium could be generally detected in patients' NP microbiota. The most abundant genera in OP microbiota showed a decline tendency in patients, including Streptococcus, Neisseria, and Haemophilus. The URT's bacterial concurrence network changed dramatically in patients. NP and OP samples were clustered into subgroups by different dominant genera; and NP and OP microbiota provided the precise indicators to distinguish IAV patients from healthy children.

CONCLUSION

This is the first respiratory microbiome analysis on pediatric IAV infection which reveals distinct NP and OP microbiota in influenza patients. It provides a new insight into IAV research from the microecology aspect and promotes the understanding of IAV pathogenesis.