Seasonality of Influenza and Respiratory Syncytial Viruses and the Effect of Climate Factors in Subtropical-Tropical Asia Using Influenza-Like Illness Surveillance Data, 2010 -2012

A combination of annual and nonannual forces drive respiratory disease in the tropics

INTRODUCTION

It is well known that influenza and other respiratory viruses are wintertime-seasonal in temperate regions. However, respiratory disease seasonality in the tropics is less well understood. In this study, we aimed to characterise the seasonality of influenza-like illness (ILI) and influenza virus in Ho Chi Minh City, Vietnam.

METHODS

We monitored the daily number of ILI patients in 89 outpatient clinics from January 2010 to December 2019. We collected nasal swabs and tested for influenza from a subset of clinics from May 2012 to December 2019. We used spectral analysis to describe the periodic signals in the system. We evaluated the contribution of these periodic signals to predicting ILI and influenza patterns through lognormal and gamma hurdle models.

RESULTS

During 10 years of community surveillance, 66 799 ILI reports were collected covering 2.9 million patient visits; 2604 nasal swabs were collected, 559 of which were PCR-positive for influenza virus. Both annual and nonannual cycles were detected in the ILI time series, with the annual cycle showing 8.9% lower ILI activity (95% CI 8.8% to 9.0%) from February 24 to May 15. Nonannual cycles had substantial explanatory power for ILI trends (ΔAIC=183) compared with all annual covariates (ΔAIC=263) in lognormal regression. Near-annual signals were observed for PCR-confirmed influenza but were not consistent over time or across influenza (sub)types. The explanatory power of climate factors for ILI and influenza virus trends was weak.

CONCLUSION

Our study reveals a unique pattern of respiratory disease dynamics in a tropical setting influenced by both annual and nonannual drivers, with influenza dynamics showing near-annual periodicities. Timing of vaccination campaigns and hospital capacity planning may require a complex forecasting approach.

Repeatability and timing of tropical influenza epidemics

Much of the world experiences influenza in yearly recurring seasons, particularly in temperate areas. These patterns can be considered repeatable if they occur predictably and consistently at the same time of year. In tropical areas, including southeast Asia, timing of influenza epidemics is less consistent, leading to a lack of consensus regarding whether influenza is repeatable. This study aimed to assess repeatability of influenza in Vietnam, with repeatability defined as seasonality that occurs at a consistent time of year with low variation. We developed a mathematical model incorporating parameters to represent periods of increased transmission and then fitted the model to data collected from sentinel hospitals throughout Vietnam as well as four temperate locations. We fitted the model for individual (sub)types of influenza as well as all combined influenza throughout northern, central, and southern Vietnam. Repeatability was evaluated through the variance of the timings of peak transmission. Model fits from Vietnam show high variance (sd = 64-179 days) in peak transmission timing, with peaks occurring at irregular intervals and throughout different times of year. Fits from temperate locations showed regular, annual epidemics in winter months, with low variance in peak timings (sd = 32-57 days). This suggests that influenza patterns are not repeatable or seasonal in Vietnam. Influenza prevention in Vietnam therefore cannot rely on anticipation of regularly occurring outbreaks.

The influence of air quality and meteorological variations on influenza A and B virus infections in a paediatric population in Singapore

INTRODUCTION

Influenza is an important cause of paediatric illness across the globe. However, information about the relationships between air pollution, meteorological variability and paediatric influenza A and B infections in tropical settings is limited.

METHODS

We analysed all daily reports of influenza A and B infections in children <5 years old obtained from the largest specialist women and children's hospital in Singapore. In separate negative binomial regression models, we assessed the dependence of paediatric influenza A and B infections on air quality and meteorological variability, using multivariable fractional polynomial modelling and adjusting for time-varying confounders.

RESULTS

Approximately 80% of 7329 laboratory-confirmed reports were caused by influenza A. We observed positive associations between sulphur dioxide (SO₂) exposure and the subsequent risk of infection with both influenza types. We observed evidence of a harvesting effect of SO₂ on Influenza A but not Influenza B. Ambient temperature was associated with a decline in influenza A reports (Relative Risk at lag 5 [RR_lag5]: 0.949, 95% CI: 0.916-0.983). Rainfall was positively associated with a subsequent increase in influenza A reports (RR_lag3: 1.044, 95% CI: 1.017-1.071). Nitrogen dioxide (NO₂) concentration was positively associated with influenza B reports (RR_lag5: 1.015, 95% CI: 1.005-1.025). There was a non-linear association between CO and influenza B reports. Absolute humidity increased the ensuing risk of influenza B (RR_lag5: 4.799, 95% CI: 2.277-10.118). Influenza A and B infections displayed dissimilar but predictable within-year seasonal patterns.

CONCLUSIONS

We observed different independent associations between air quality and meteorological variability with paediatric influenza A and B infections. Anticipated seasonal infection peaks and variations in air quality and meteorological parameters can inform the timing of community measures aimed at reducing influenza infection risk.

Burden of Respiratory Syncytial Virus Related Acute Lower Respiratory Tract Infection in Hospitalized Thai Children: A 6-Year National Data Analysis

Objectives: This study sought to determine the epidemiology, seasonal variations, morbidity, and mortality of respiratory syncytial virus (RSV) infection among hospitalized children with lower respiratory tract infection in Thailand. In addition, we assessed the risk factors associated with severe RSV lower respiratory tract infection (LRTI)-related morbidity and mortality. Methods: The data were reviewed retrospectively from the National Health Security Office for hospitalized children younger than 18 years old diagnosed with RSV-related LRTI in Thailand, between the fiscal years of 2015 to 2020. The RSV-related LRTIs were identified using the International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Thai Modification. ICD-10-TM codes J12.1, J20.5, and J21.0, which represent respiratory syncytial virus pneumonia, acute bronchitis due to respiratory syncytial virus, and acute bronchiolitis due to respiratory syncytial virus, respectively, were studied. Results: During the study period, RSV-related LRTI accounted for 19,340 of the 1,610,160 hospital admissions due to LRTI. RSV pneumonia was the leading cause of hospitalization (13,684/19,340; 70.76%), followed by bronchiolitis (2849/19,340; 14.73%) and bronchitis (2807/19,340; 14.51%), respectively. The highest peak incidence of 73.55 percent occurred during Thailand’s rainy season, from August to October. The mortality rate of RSV-related LRTI in infants younger than 1 year of age was 1.75 per 100,000 person years, which was significantly higher than that of children 1 to younger than 5 years old and children 5 to younger than 18 years old (0.21 per 100,000 person years and 0.01 per 100,000 person years, respectively, p-value < 0.001). Factors associated with mortality were congenital heart disease, hematologic malignancy, malnutrition, and neurological disease. Conclusions: In children with RSV LRTI, pneumonia was the leading cause of hospitalization. The admission rate was highest during the rainy season. Mortality from RSV-related LRTI was higher in children under 1 year old and in children with underlying illnesses; future preventive interventions should target these groups of patients.

Drivers of respiratory syncytial virus seasonal epidemics in children under 5 years in Kilifi, coastal Kenya

Respiratory syncytial virus (RSV) causes significant childhood morbidity and mortality in the developing world. The determinants of RSV seasonality are of importance in designing interventions. They are poorly understood in tropical and sub-tropical regions in low- and middle-income countries. Our study utilized long-term surveillance data on cases of RSV associated with severe or very severe pneumonia in children aged 1 day to 59 months admitted to the Kilifi County Hospital. A generalized additive model was used to investigate the association between RSV admissions and meteorological variables (maximum temperature, rainfall, absolute humidity); weekly number of births within the catchment population; and school term dates. Furthermore, a time-series-susceptible-infected-recovered (TSIR) model was used to reconstruct an empirical transmission rate which was used as a dependent variable in linear regression and generalized additive models with meteorological variables and school term dates. Maximum temperature, absolute humidity, and weekly number of births were significantly associated with RSV activity in the generalized additive model. Results from the TSIR model indicated that maximum temperature and absolute humidity were significant factors. Rainfall and school term did not yield significant relationships. Our study indicates that meteorological parameters and weekly number of births potentially play a role in the RSV seasonality in this region. More research is required to explore the underlying mechanisms underpinning the observed relationships.

Forecasting the Potential Number of Influenza-like Illness Cases by Fusing Internet Public Opinion

As influenza viruses mutate rapidly, a prediction model for potential outbreaks of influenza-like illnesses helps detect the spread of the illnesses in real time. In order to create a better prediction model, in this study, in addition to using the traditional hydrological and atmospheric data, features, such as popular search keywords on Google Trends, public holiday information, population density, air quality indices, and the numbers of COVID-19 confirmed cases, were also used to train the model in this research. Furthermore, Random Forest and XGBoost were combined and used in the proposed prediction model to increase the prediction accuracy. The training data used in this research were the historical data taken from 2016 to 2021. In our experiments, different combinations of features were tested. The results show that features, such as popular search keywords on Google Trends, the numbers of COVID-19 confirmed cases, and air quality indices can improve the outcome of the prediction model. The evaluation results showed that the error rate between the predicted results and the actual number of influenza-like cases form Week 15 to Week 18 fell to less than 5%. The outbreak of COVID-19 in Taiwan began in Week 19 and resulted in a sharp rise in the number of clinic or hospital visits by patients of influenza-like illnesses. After that, from Week 21 to Week 26, the error rate between the predicted and actual numbers of influenza-like cases in the later period dropped down to 13%. It can be confirmed from the actual experimental results in this research that the use of the ensemble learning prediction model proposed in this research can accurately predict the trend of influenza-like cases.

North to south gradient and local waves of influenza in Chile

Influenza seasonality is caused by complex interactions between environmental factors, viral mutations, population crowding, and human travel. To date, no studies have estimated the seasonality and latitudinal patterns of seasonal influenza in Chile. We obtained influenza-like illness (ILI) surveillance data from 29 Chilean public health networks to evaluate seasonality using wavelet analysis. We assessed the relationship between the start, peak, and latitude of the ILI epidemics using linear and piecewise regression. To estimate the presence of incoming and outgoing traveling waves (timing vs distance) between networks and to assess the association with population size, we used linear and logistic regression. We found a north to south gradient of influenza and traveling waves that were present in the central, densely populated region of Chile. Our findings suggest that larger populations in central Chile drive seasonal influenza epidemics.

Association between climatic factors and respiratory syncytial virus detection rates in Cheonan, Korea

The use of big data may facilitate the recognition and interpretation of causal relationships between disease occurrence and climatic variables. This study examined the effects of various climatic variables on the seasonal epidemiology of respiratory syncytial virus (RSV) infections in the temperate climate of Korea. Trends in RSV detection were analyzed using 9010 samples tested between January 1, 2012, and December 31, 2018, at Dankook University Hospital in Cheonan, Korea. Seasonal patterns in RSV detection frequency were compared with local climatic variables during the same period. RSV detection rate of 12.8% (n = 1150/9010) was observed, which was higher for RSV-A (7.1%) than RSV-B (5.8%) and RSV-A and RSV-B alternated each year. Children < 1 year exhibited high infection rates with RSV-A (68.5%) and RSV-B (58.7%). RSV-A and RSV-B infection rates in children under 9 years old were 96.2% and 92.1%, respectively. RSV had a significant relationship with several climatic factors. Air temperature, wind chill temperature, and particulate matter concentration were lower on days with a higher frequency of RSV detection. In contrast, atmospheric pressure was higher on days with lower RSV detection. Although the detection rates for RSV-A and RSV-B increased on days with lower air temperatures, those for RSV-B also increased on days with lower wind chill temperatures. Our findings suggest that climatic variables affect the RSV detection rate among children under 10 years of age. The present data may help predict the time when prevention strategies may be the most effective.

Epidemiology of acute lower respiratory tract infection hospitalizations in Thai children: A 5-year national data analysis

BACKGROUND

Lower respiratory tract infections (LRTIs) are the most common cause for hospitalization in pediatric patients. Pediatric patients with LRTIs are at an increased risk of morbidity and mortality. The national data analysis of epidemiologic variations facilitates awareness and develops solutions to prevent these conditions in the future.

OBJECTIVE

This study aims to evaluate the epidemiology, causative pathogens, morbidity, and mortality of LRTIs in pediatric patients of Thailand from 2015 to 2019.

METHODS

This was a retrospective study among pediatric patients aged between 0 and 18 years old admitted in hospitals due to LRTIs in Thailand from January 2015 to December 2019. The data were extracted from National Health Security Office using the International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Thai Modification; ICD-10-TM of J09 to J22.

RESULTS

A total of 1,423,509 children hospitalized due to LRTIs were identified. Most of the patients were of age 1-5 years. Pneumonia was the most common LRTI (876,557 children, 61.58%) in hospitalized children. Respiratory syncytial virus (RSV) is the main etiologic pathogen of bronchiolitis, which presents in approximately 10.86% of all episodes. Influenza viruses were found predominantly in children with pneumonia (15.52%). The mortality rate since 2015-2019 was highest in pneumonia under 1 year old (P < 0.001). Pneumonia in children under 5 years old had the highest mortality rate, which accounted for 11.85 per 100,000 children in 2019.

CONCLUSIONS

LRTIs had a high incidence rate of hospitalization and mortality, especially in children under 5 years old. Influenza virus was the most common pathogen of pneumonia.

Transplacental Antibody Transfer of Respiratory Syncytial Virus Specific IgG in Non-Human Primate Mother-Infant Pairs

One approach to protect new-borns against respiratory syncytial virus (RSV) is to vaccinate pregnant women in the last trimester of pregnancy. The boosting of circulating antibodies which can be transferred to the foetus would offer immune protection against the virus and ultimately the disease. Since non-human primates (NHPs) have similar reproductive anatomy, physiology, and antibody architecture and kinetics to humans, we utilized this preclinical species to evaluate maternal immunization (MI) using an RSV F subunit vaccine. Three species of NHPs known for their ability to be infected with human RSV in experimental challenge studies were tested for RSV-specific antibodies. African green monkeys had the highest overall antibody levels of the old-world monkeys evaluated and they gave birth to offspring with anti-RSV titers that were proportional to their mother. These higher overall antibody levels are associated with greater durability found in their offspring. Immunization of RSV seropositive AGMs during late pregnancy boosts RSV titers, which consequentially results in significantly higher titers in the vaccinated new-borns compared to the new-borns of unvaccinated mothers. These findings, accomplished in small treatment group sizes, demonstrate a model that provides an efficient, resource sparing and translatable preclinical in vivo system for evaluating vaccine candidates for maternal immunization.

Viral Respiratory Pathogens and Lung Injury

Several viruses target the human respiratory tract, causing different clinical manifestations spanning from mild upper airway involvement to life-threatening acute respiratory distress syndrome (ARDS). As dramatically evident in the ongoing SARS-CoV-2 pandemic, the clinical picture is not always easily predictable due to the combined effect of direct viral and indirect patient-specific immune-mediated damage. In this review, we discuss the main RNA (orthomyxoviruses, paramyxoviruses, and coronaviruses) and DNA (adenoviruses, herpesviruses, and bocaviruses) viruses with respiratory tropism and their mechanisms of direct and indirect cell damage. We analyze the thin line existing between a protective immune response, capable of limiting viral replication, and an unbalanced, dysregulated immune activation often leading to the most severe complication. Our comprehension of the molecular mechanisms involved is increasing and this should pave the way for the development and clinical use of new tailored immune-based antiviral strategies.

Epidemiology and Seasonality of Childhood Respiratory Syncytial Virus Infections in the Tropics

Infections caused by respiratory syncytial virus (RSV) are a major cause of morbidity and mortality in young children worldwide. Understanding seasonal patterns of region-specific RSV activity is important to guide resource allocation for existing and future treatment and prevention strategies. The decades of excellent RSV surveillance data that are available from the developed countries of the world are incredibly instructive in advancing public health initiatives in those regions. With few exceptions, these developed nations are positioned geographically across temperate regions of the world. RSV surveillance across tropical regions of the world has improved in recent years, but remains spotty, and where available, still lacks the necessary longitudinal data to determine the amount of seasonal variation expected over time. However, existing and emerging data collected across tropical regions of the world do indicate that patterns of infection are often quite different from those so well described in temperate areas. Here, we provide a brief summary regarding what is known about general patterns of RSV disease activity across tropical Asia, Africa and South America, then offer additional country-specific details using examples where multiple reports and/or more robust surveillance data have become available.

Indoor Environmental Factors and Acute Respiratory Illness in a Prospective Cohort of Community-Dwelling Older Adults

BACKGROUND

Ambient environmental factors have been associated with respiratory infections in ecological studies, but few studies have explored the impact of indoor environmental factors in detail. The current study aimed to investigate the impact of indoor environment on the risk of acute respiratory illness (ARI) in a subtropical city.

METHOD

A prospective cohort study was conducted in 285 community-dwelling older adults from December 2016 through May 2019. Individual household indoor environment data and ARI incidence were continuously collected. A time-stratified case-crossover analysis was conducted to estimate the excess risk of ARI associated with per-unit increase of daily mean indoor temperature, relative humidity, and absolute humidity (AH).

RESULT

In total, 168 episodes of ARI were reported with an average risk of 36.8% per year. We observed a negative association of ARI with indoor AH up to 5 lag days in cool seasons, with a 6-day cumulative excess risk estimate of -9.0% (95% confidence interval, -15.9% to -1.5%). Negative associations between household temperature or relative humidity and ARI were less consistent across warm and cool seasons.

CONCLUSIONS

Lower indoor AH in household was associated with a higher risk of ARI in the community-dwelling older adults in Hong Kong during cold seasons.

Non-linear effect of different humidity types on scrub typhus occurrence in endemic provinces, Thailand

Background

Reported monthly scrub typhus (ST) cases in Thailand has an increase in the number of cases during 2009–2014. Humidity is a crucial climatic factor for the survival of chiggers, which is the disease vectors. The present study was to determine the role of humidity in ST occurrence in Thailand and its delayed effect.

Methods

We obtained the climate data from the Department of Meteorology, the disease data from Ministry of Public Health. Negative binomial regression combined with a distributed lag non-linear model (NB-DLNM) was employed to determine the non-linear effects of different types of humidity on the disease. This model controlled overdispersion and confounder, including seasonality, minimum temperature, and cumulative total rainwater.

Results

The occurrence of the disease in the 6-year period showed the number of cases gradually increased summer season (Mid-February – Mid-May) and then reached a plateau during the rainy season (Mid-May – Mid-October) and then steep fall after the cold season (Mid-October – Mid-February). The high level (at 70%) of minimum relative humidity (RHmin) was associated with a 33% (RR 1.33, 95% CI 1.13–1.57) significant increase in the number of the disease; a high level (at 14 g/m³) of minimum absolute humidity (AHmin) was associated with a 30% (RR 1.30, 95% CI 1.14–1.48); a high level (at 1.4 g/kg) of minimum specific humidity (SHmin) was associated with a 28% (RR 1.28, 95% CI 1.04–1.57). The significant effects of these types of humidity occurred within the past month.

Conclusion

Humidity played a significant role in enhancing ST cases in Thailand, particularly at a high level and usually occurred within the past month. NB-DLNM had good controlled for the overdispersion and provided the precise estimated relative risk of non-linear associations. Results from this study contributed the evidence to support the Ministry of Public Health on warning system which might be useful for public health intervention and preparation in Thailand.

Viral etiology and seasonal trends of pediatric acute febrile illness in southern Puerto Rico; a seven-year review

BACKGROUND

Acute febrile illness (AFI) is an important cause for seeking health care among children. Knowledge of the most common etiologic agents of AFI and its seasonality is limited in most tropical regions.

METHODOLOGY/PRINCIPAL FINDINGS

To describe the viral etiology of AFI in pediatric patients (≤18 years) recruited through a sentinel enhanced dengue surveillance system (SEDSS) in Southern Puerto Rico, we analyzed data for patients enrolled from 2012 to May 2018. To identify seasonal patterns, we applied time-series analyses to monthly arboviral and respiratory infection case data. We calculated coherence and phase differences for paired time-series to quantify the association between each time series. A viral pathogen was found in 47% of the 14,738 patients. Influenza A virus was the most common pathogen detected (26%). The incidence of Zika and dengue virus etiologies increased with age. Arboviral infections peaked between June and September throughout the times-series. Respiratory infections have seasonal peaks occurring in the fall and winter months of each year, though patterns vary by individual respiratory pathogen.

CONCLUSIONS/SIGNIFICANCE

Distinct seasonal patterns and differences in relative frequency by age groups seen in this study can guide clinical and laboratory assessment in pediatric patients with AFI in Puerto Rico.

Correlation between Children Respiratory Virus Infections and Climate Factors

Objective Respiratory viruses are the most important cause of lower respiratory tract infections (LRTI) in children. Meteorological factors can influence viral outbreaks. The objective of this study was to determine the association between climate variables and respiratory virus detection.

Methods Multicenter prospective 1-year surveillance was conducted among children hospitalized for LRTI in Tunisia. Nasopharyngeal aspirates were tested by direct immunofluorescence assay (DIFA) for the detection of respiratory syncytial virus (RSV); adenovirus (AdV); influenza virus (IFV) A and B; and parainfluenza virus 1, 2, and 3 (PIV1/2/3). Samples were further analyzed by reverse-transcription polymerase chain reaction for the detection of human metapneumovirus (hMPV). Monthly meteorological data were determined by consulting the National Institute of Meteorology and the World Weather Online Meteorological Company websites. Pearson's correlation tests were used to determine the statistical association between the detection of respiratory viruses and climatic characteristics.

Results Among 572 patients, 243 (42.5%) were positive for at least one virus. The most frequently detected viruses by DIFA were RSV (30.0%), followed by IFVA (3.8%), IFVB (3.5%), PIV (0.9%), and AdV (0.9%). HMPV was detected in 13 RSV-negative samples (3.3%). Dual infections were detected in seven cases (1.2%). Monthly global respiratory viruses and RSV detections correlated significantly with temperature, rainfall, cloud cover, wind speed, wind temperature, and duration of sunshine. Monthly IFV detection significantly correlated with rainfall, wind speed, wind temperature, and duration of sunshine. HMPV detection significantly correlated with temperature and wind temperature.

Conclusion Respiratory viral outbreaks are clearly related to meteorological factors in Tunisia.

Climate factors influence seasonal influenza activity in Bangkok, Thailand

Yearly increase in influenza activity is associated with cold and dry winter in the temperate regions, while influenza patterns in tropical countries vary significantly by regional climates and geographic locations. To examine the association between influenza activity in Thailand and local climate factors including temperature, relative humidity, and rainfall, we analyzed the influenza surveillance data from January 2010 to December 2018 obtained from a large private hospital in Bangkok. We found that approximately one in five influenza-like illness samples (21.6% or 6,678/30,852) tested positive for influenza virus. Influenza virus typing showed that 34.2% were influenza A(H1N1)pdm09, 46.0% were influenza A(H3N2), and 19.8% were influenza B virus. There were two seasonal waves of increased influenza activity. Peak influenza A(H1N1)pdm09 activity occurred in February and again in August, while influenza A(H3N2) and influenza B viruses were primarily detected in August and September. Time series analysis suggests that increased relative humidity was significantly associated with increased influenza activity in Bangkok. Months with peak influenza activity generally followed the most humid months of the year. We performed the seasonal autoregressive integrated moving average (SARIMA) multivariate analysis of all influenza activity on the 2011 to 2017 data to predict the influenza activity for 2018. The resulting model closely resembled the actual observed overall influenza detected that year. Consequently, the ability to predict seasonal pattern of influenza in a large tropical city such as Bangkok may enable better public health planning and underscores the importance of annual influenza vaccination prior to the rainy season.

Seasonality and coinfection of bronchiolitis: epidemiological specificity and consequences in terms of prophylaxis in tropical climate

OBJECTIVE

To describe the viruses involved, seasonality and coinfection in hospitalised children with suspected bronchiolitis.

METHODS

Over the period 1/07/2007 to 31/12/2008, all children hospitalised for bronchiolitis in the paediatric ward were prospectively included, and had respiratory syncytial virus (RSV) screenings. We retrospectively tested all samples for RSVA, RSVB, rhinovirus (RV), human metapneumovirus, parainfluenza 1, 2, 3, 4, influenza A and influenza B.

RESULTS

198 children were tested, and 23% were negative for all viruses. RSVA was predominant in 2008 (64% of all viruses) and RSVB in 2007 (66% of all viruses). RV was frequent during both seasons (24% of all viruses). Flu was not found during the study period. Virus distribution was similar regardless of season or age, and identical to typical patterns in temperate countries. Coinfections were less frequent than in temperate regions because respiratory virus seasons seem to be better separated. The bronchiolitis season started in August and finished in December with a peak in October.

CONCLUSION

The specific seasonality of bronchiolitis infection requires palivizumab prophylaxis starting in early July for high-risk infants.

Identification of viral etiology of acute respiratory tract infections in children and adults in Tabanan, Bali, Indonesia

Acute respiratory tract infection (ARTI) is the most common infectious disease in humans worldwide. The morbidity and mortality rates are high, especially in developing countries from Southeast Asia and Africa. While ARTI is commonly associated with viruses, there is limited data on the spectrum of viruses causing ARTI in developing countries, including Indonesia. This study was based on utilizing molecular techniques targeting a panel of 11 endemic and emerging respiratory viral pathogens including zoonotic viruses in a cohort of children and adults presenting at Tabanan General Hospital, Bali, with acute respiratory illness, from January to November 2017. In total, 98 out of 200 samples (49.0 %) tested positive for viruses. Our study confirmed 64.3 % viral etiology in children and 12.2 % in adults. Viruses that were detected were Herpesviridae (15.0 %) followed by enteroviruses (12.0 %), influenza A virus (11.5 %), respiratory syncytial virus (8.0 %), Adenoviridae (6.5 %), human metapneumovirus (3.5 %), Paramyxoviridae (2.0 %), bocavirus (1.0 %) and Coronaviridae (0.5 %). The study sheds light on the viral spectrum of ARTI in children and adults in Tabanan, Bali, Indonesia.

Human respiratory syncytial virus and influenza seasonality patterns-Early findings from the WHO global respiratory syncytial virus surveillance

Background

Human respiratory syncytial virus (RSV) causes illnesses among all age groups and presents a burden to healthcare services. To better understand the epidemiology and seasonality of RSV in different geographical areas, the World Health Organization (WHO) coordinated a pilot initiative to access the feasibility of establishing RSV surveillance using the existing Global Influenza Surveillance and Response System (GISRS) platform.

Objectives

To describe and compare RSV and influenza seasonality in countries in the northern andsouthern temperate, and tropics during the period January 2017 to April 2019.

Methods

Fourteen countries in six WHO regions participating in the GISRS were invited for the pilot. Hospitalized patients presenting with severe acute respiratory illness (SARI), SARI without fever and outpatients presenting with acute respiratory illness (ARI) were enrolled from January 2017 to April 2019. The expected minimum sample size was 20 samples per week, year‐round, per country. Real‐time RT‐PCR was used to detect RSV and influenza viruses. Results were uploaded to the WHO FluMart platform.

Results

Annual seasonality of RSV was observed in all countries, which overlapped to a large extent with the influenza activity. In countries, in temperate regions RSV peaked in the autumn/winter months. In Egypt, a subtropical country, RSV activity peaked in the cooler season. In the tropical regions, RSV peaked during the rainy seasons.

Conclusion

Early findings from the WHO RSV surveillance pilot based on the GISRS suggest annual seasonal patterns for of RSV circulation that overlap with influenza. RSV surveillance needs to be continued for several more seasons to establish seasonality patterns to inform prevention and control strategies.

Influenza in temperate and tropical Asia: a review of epidemiology and vaccinology

The impact of seasonal influenza has been under-appreciated in Asia and surveillance data lags in most other regions. The variety of influenza circulation patterns in Asia – largely due to the range of climates – has also only recently been recognized and its effect on the burden of disease is not fully understood. Recent reports that clinical protection wanes in the weeks after influenza vaccination emphasize the importance of optimally timing vaccination to local epidemiology. It also raises questions as to whether influenza vaccines should be administered more frequently than annually and what may be the benefits in Asia of access to new vaccines with enhanced immunogenicity and effectiveness. This review will summarize influenza surveillance data from Asian countries over 2011–2018, and consider the implications for vaccination strategies in different parts of Asia.

Seasonal variation and etiologic inferences of childhood pneumonia and diarrhea mortality in India

Control of pneumonia and diarrhea mortality in India requires understanding of their etiologies. We combined time series analysis of seasonality, climate region, and clinical syndromes from 243,000 verbal autopsies in the nationally representative Million Death Study. Pneumonia mortality at 1 month-14 years was greatest in January (Rate ratio (RR) 1.66, 99% CI 1.51-1.82; versus the April minimum). Higher RRs at 1-11 months suggested respiratory syncytial virus (RSV) etiology. India's humid subtropical region experienced a unique summer pneumonia mortality. Diarrhea mortality peaked in July (RR 1.66, 1.48-1.85) and January (RR 1.37, 1.23-1.48), while deaths with fever and bloody diarrhea (indicating enteroinvasive bacterial etiology) showed little seasonality. Combining mortality at ages 1-59 months with prevalence surveys, we estimate 40,600 pneumonia deaths from Streptococcus pneumoniae, 20,700 from RSV, 12,600 from influenza, and 7200 from Haemophilus influenzae type b and 24,700 diarrheal deaths from rotavirus occurred in 2015. Careful mortality studies can elucidate etiologies and inform vaccine introduction.

Scoping Review of Climate Change and Health Research in the Philippines: A Complementary Tool in Research Agenda-Setting

The impacts of climate change on human health have been observed and projected in the Philippines as vector-borne and heat-related diseases have and continue to increase. As a response, the Philippine government has given priority to climate change and health as one of the main research funding topics. To guide in identifying more specific research topics, a scoping review was done to complement the agenda-setting process by mapping out the extent of climate change and health research done in the country. Research articles and grey literature published from 1980 to 2017 were searched from online databases and search engines, and a total of 34 quantitative studies were selected. Fifty-three percent of the health topics studied were about mosquito-borne diseases, particularly dengue fever. Seventy-nine percent of the studies reported evidence of positive associations between climate factors and health outcomes. Recommended broad research themes for funding were health vulnerability, health adaptation, and co-benefits. Other notable recommendations were the development of open data and reproducible modeling schemes. In conclusion, the scoping review was useful in providing a background for research agenda-setting; however, additional analyses or consultations should be complementary for added depth.

Burden of Respiratory Syncytial Virus Disease and Mortality Risk Factors in Argentina: 18 Years of Active Surveillance in a Children's Hospital

BACKGROUND

Respiratory syncytial virus is the leading cause of acute lower respiratory infection in children. We aimed to describe the clinical-epidemiologic pattern and risk factors for mortality associated with RSV infection.

METHODS

This is a prospective, cross-sectional study of acute lower respiratory infection in children admitted to the Children's Hospital during 2000 to 2017. Viral diagnosis was made by fluorescent antibody techniques or real-time-polymerase chain reaction. We compared clinical-epidemiologic characteristics of RSV infection in nonfatal versus fatal cases. Multiple logistic regression was used to identify independent predictors of mortality.

RESULTS

Of 15,451 patients with acute lower respiratory infection, 13,033 were tested for respiratory viruses and 5831 (45%) were positive: RSV 81.3% (4738), influenza 7.6% (440), parainfluenza 6.9% (402) and adenovirus 4.3% (251). RSV had a seasonal epidemic pattern coinciding with months of lowest average temperature. RSV cases show a case fatality rate of 1.7% (82/4687). Fatal cases had a higher proportion of prematurity (P < 0.01), perinatal respiratory history (P < 0.01), malnourishment (P < 0.01), congenital heart disease (P < 0.01), chronic neurologic disease (P < 0.01) and pneumonia at clinical presentation (P = 0.014). No significant difference between genders was observed. Most deaths occurred among children who had complications: respiratory distress (80.5%), nosocomial infections (45.7%), sepsis (31.7%) and atelectasis (13.4%). Independent predictors of RSV mortality were moderate-to-severe malnourishment, odds ratio (OR): 3.69 [95% confidence interval (CI): 1.98-6.87; P < 0.0001]; chronic neurologic disease, OR: 4.14 (95% CI: 2.12-8.08; P < 0.0001); congenital heart disease, OR: 4.18 (95% CI: 2.39-7.32; P< 0.0001); and the age less than 6 months, OR: 1.99 (95% CI: 1.24-3.18; P = 0.004).

CONCLUSIONS

RSV showed an epidemic pattern affecting mostly young children. Malnourishment, chronic neurologic disease, congenital heart disease and the age less than 6 months were the independent risk factors for RSV mortality.

Effects and interaction of meteorological factors on influenza: Based on the surveillance data in Shaoyang, China

BACKGROUND

Previous studies have demonstrated that meteorological factors influence the incidence of influenza. However, little is known regarding the interactions of meteorological factors on the risk of influenza in China.

OBJECTIVE

The study aimed to evaluate the associations between meteorological factors and influenza in Shaoyang of southern China, and explore the interaction of temperature with humidity and rainfall.

METHODS

Weekly meteorological data and disease surveillance data of influenza in Shaoyang were collected from 2009 to 2012. According to the incubation period and infectious period of influenza virus, the maximum lag period was set as 3 weeks. A generalized additive model was conducted to evaluate the effect of meteorological factors on the weekly number of influenza cases and a stratification model was applied to investigate the interaction.

RESULTS

During the study period, the total number of influenza cases that were notified in the study area was 2506, with peak times occurring from December to March. After controlling for the confounders, each 5 °C decrease in minimum temperature was related to 8% (95%CI: 1-15%) increase in the number of influenza cases at a 1-week lag. There was an interaction between minimum temperature and relative humidity and the risk of influenza was higher in cold and less humid conditions than other conditions. The interaction between minimum temperature and rainfall was not statistically significant in our study.

CONCLUSIONS

The study suggests that minimum temperature is inversely associated with influenza in the study area of China, and the effect can be modified by relative humidity. Meteorological variables could be integrated in current public health surveillance system to better prepare for the risks of influenza.

The effects of socioecological factors on variation of communicable diseases: A multiple-disease study at the national scale of Vietnam

OBJECTIVE

To examine the effects of socioecological factors on multiple communicable diseases across Vietnam.

METHODS

We used the Moran's I tests to evaluate spatial clusters of diseases and applied multilevel negative binomial regression models using the Bayesian framework to analyse the association between socioecological factors and the diseases queried by oral, airborne, vector-borne, and animal transmission diseases.

RESULTS AND SIGNIFICANCE

The study found that oral-transmission diseases were spatially distributed across the country; whereas, the airborne-transmission diseases were more clustered in the Northwest and vector-borne transmission diseases were more clustered in the South. Most of diseases were sensitive with climatic factors. For instance, a 1°C increase in average temperature is significantly associated with 0.4% (95CI, 0.3-0.5), 2.5% (95%CI, 1.4-3.6), 0.9% (95%CI, 0.6-1.4), 1.1% (95%CI), 5% (95%CI, 3-.7.4), 0.4% (95%CI, 0.2-0.7), and 2% (95%CI, 1.5-2.8) increase in risk of diarrhoea, shigellosis, mumps, influenza, dengue, malaria, and rabies respectively. The influences of socio-economic factors on risk of communicable diseases are varied by factors with the biggest influence of population density. The research findings reflect an important implication for the climate change adaptation strategies of health sectors. A development of weather-based early warning systems should be considered to strengthen communicable disease prevention in Vietnam.

Effect of Weather Variability on Seasonal Influenza Among Different Age Groups in Queensland, Australia: A Bayesian Spatiotemporal Analysis

Background

The effects of weather variability on seasonal influenza among different age groups remain unclear. The comparative study aims to explore the differences in the associations between weather variability and seasonal influenza, and growth rates of seasonal influenza epidemics among different age groups in Queensland, Australia.

Methods

Three Bayesian spatiotemporal conditional autoregressive models were fitted at the postal area level to quantify the relationships between seasonal influenza and monthly minimum temperature (MIT), monthly vapor pressure, school calendar pattern, and Index of Relative Socio-Economic Advantage and Disadvantage for 3 age groups (<15, 15-64, and ≥65 years).

Results

The results showed that the expected decrease in monthly influenza cases was 19.3% (95% credible interval [CI], 14.7%-23.4%), 16.3% (95% CI, 13.6%-19.0%), and 8.5% (95% CI, 1.5%-15.0%) for a 1°C increase in monthly MIT at <15, 15-64, and ≥65 years of age, respectively, while the average increase in the monthly influenza cases was 14.6% (95% CI, 9.0%-21.0%), 12.1% (95% CI, 8.8%-16.1%), and 9.2% (95% CI, 1.4%-16.9%) for a 1-hPa increase in vapor pressure.

Conclusions

Weather variability appears to be more influential on seasonal influenza transmission in younger (0-14) age groups. The growth rates of influenza at postal area level were relatively small for older (≥65) age groups in Queensland, Australia.

Epidemiological Features and Forecast Model Analysis for the Morbidity of Influenza in Ningbo, China, 2006-2014

This study aimed to identify circulating influenza virus strains and vulnerable population groups and investigate the distribution and seasonality of influenza viruses in Ningbo, China. Then, an autoregressive integrated moving average (ARIMA) model for prediction was established. Influenza surveillance data for 2006–2014 were obtained for cases of influenza-like illness (ILI) (n = 129,528) from the municipal Centers for Disease Control and virus surveillance systems of Ningbo, China. The ARIMA model was proposed to predict the expected morbidity cases from January 2015 to December 2015. Of the 13,294 specimens, influenza virus was detected in 1148 (8.64%) samples, including 951 (82.84%) influenza type A and 197 (17.16%) influenza type B viruses; the influenza virus isolation rate was strongly correlated with the rate of ILI during the overall study period (r = 0.20, p < 0.05). The ARIMA (1, 1, 1) (1, 1, 0)₁₂ model could be used to predict the ILI incidence in Ningbo. The seasonal pattern of influenza activity in Ningbo tended to peak during the rainy season and winter. Given those results, the model we established could effectively predict the trend of influenza-related morbidity, providing a methodological basis for future influenza monitoring and control strategies in the study area.