EPIPOI: a user-friendly analytical tool for the extraction and visualization of temporal parameters from epidemiological time series

Global analysis of respiratory viral circulation and timing of epidemics in the pre-COVID-19 and COVID-19 pandemic eras, based on data from the Global Influenza Surveillance and Response System (GISRS)

OBJECTIVES

The COVID-19 pandemic significantly changed respiratory viruses' epidemiology due to non-pharmaceutical interventions and possible viral interactions. This study investigates whether the circulation patterns of respiratory viruses have returned to pre-pandemic norms by comparing their peak timing and duration during the first three SARS-CoV-2 seasons to pre-pandemic times.

METHODS

Global Influenza Surveillance and Response System data from 194 countries (2014-2023) was analyzed for epidemic peak timing and duration, focusing on pre-pandemic and pandemic periods across both hemispheres and the intertropical belt. The analysis was restricted to countries meeting specific data thresholds to ensure robustness.

RESULTS

In 2022/2023, the northern hemisphere experienced earlier influenza and respiratory syncytial virus (RSV) peaks by 1.9 months (P <0.001). The duration of influenza epidemics increased by 2.2 weeks (P <0.001), with RSV showing a similar trend. The southern hemisphere's influenza peak shift was not significant (P = 0.437). Intertropical regions presented no substantial change in peak timing but experienced a significant reduction in the duration for human metapneumovirus and adenovirus (7.2 and 6.5 weeks shorter, respectively, P <0.001).

CONCLUSIONS

The pandemic altered the typical patterns of influenza and RSV, with earlier peaks in 2022 in temperate areas. These findings highlight the importance of robust surveillance data to inform public health strategies on evolving viral dynamics in the years to come.

Intensity and drivers of subtypes interference between seasonal influenza viruses in mainland China: A modeling study

Subtype interference has a significant impact on the epidemiological patterns of seasonal influenza viruses (SIVs). We used attributable risk percent [the absolute value of the ratio of the effective reproduction number (Rₑ) of different subtypes minus one] to quantify interference intensity between A/H1N1 and A/H3N2, as well as B/Victoria and B/Yamagata. The interference intensity between A/H1N1 and A/H3N2 was higher in southern China 0.26 (IQR: 0.11-0.46) than in northern China 0.17 (IQR: 0.07-0.24). Similarly, interference intensity between B/Victoria and B/Yamagata was also higher in southern China 0.14 (IQR: 0.07-0.24) than in norther China 0.10 (IQR: 0.04-0.18). High relative humidity significantly increased subtype interference, with the highest relative risk reaching 20.59 (95% CI: 6.12-69.33) in southern China. Southern China exhibited higher levels of subtype interference, particularly between A/H1N1 and A/H3N2. Higher relative humidity has a more pronounced promoting effect on subtype interference.

The weekly P25 of the age of the influenza-like illness shows a higher correlation with COVID-19 mortality than rapid tests and could predict the evolution of COVID-19 pandemics in sentinel surveillance, Piura, Perú, 2021

GOAL

To describe the dynamics of syndromic surveillance of ILI cases in seasonal and COVID-19 pandemic scenarios.

METHODOLOGY

A descriptive study of the epidemiological behavior of ILI in the seasonal and COVID-19 pandemic scenarios. Of a sample of 16,231 cases of ILI from 2013 to 2021, the features of cases from 68 weeks before and during the pandemic were selected and compared; weekly endemic channels were built; data fluctuations on the trend of ILI cases were analyzed; and estimated weekly correlations between weekly P25 age, cases confirmed by rapid tests, and mortality from COVID-19. To analyze clinical-epidemiological and mortality data, Student's t test, Mann-Whitney U, Chi2, Spearman's Ro, polynomial, and multinomial regression with a 95% confidence interval were used.

RESULTS

During the COVID-19 pandemic, those most affected with ILI were: adults and the elderly; higher median age; autochthonous cases predominated; a lower proportion of other syndromes; delays in seeking care; and a higher rate of pneumonia attack than in the seasonal period (p< 0.01). Rapid tests (serological and antigenic) confirmed 52.7% as COVID-19. Two ILI pandemic waves were seasonally consistent with confirmed COVID-19 cases and district mortality with robust correlation (p<0.01) before and during the pandemic, especially the ILI weekly P25 age, which has a more robust correlation with mortality than ILI and rapid tests (p<0.01) whose endemic channels describe and could predict the evolution of the pandemic (p<0.01).

CONCLUSIONS

The pandemic changed the clinical and epidemiological behavior of ILI, and the weekly P25 of age is a more robust indicator to monitor the COVID-19 pandemic than a rapid test and could predict its evolution.

The current landscape of software tools for the climate-sensitive infectious disease modelling community

Climate-sensitive infectious disease modelling is crucial for public health planning and is underpinned by a complex network of software tools. We identified only 37 tools that incorporated both climate inputs and epidemiological information to produce an output of disease risk in one package, were transparently described and validated, were named (for future searching and versioning), and were accessible (ie, the code was published during the past 10 years or was available on a repository, web platform, or other user interface). We noted disproportionate representation of developers based at North American and European institutions. Most tools (n=30 [81%]) focused on vector-borne diseases, and more than half (n=16 [53%]) of these tools focused on malaria. Few tools (n=4 [11%]) focused on food-borne, respiratory, or water-borne diseases. The under-representation of tools for estimating outbreaks of directly transmitted diseases represents a major knowledge gap. Just over half (n=20 [54%]) of the tools assessed were described as operationalised, with many freely available online.

The global region-specific epidemiologic characteristics of influenza: World Health Organization FluNet data from 1996 to 2021

OBJECTIVES

This study aimed to investigate region-specific epidemiologic characteristics of influenza and influenza transmission zones (ITZs).

METHODS

Weekly influenza surveillance data of 156 countries from 1996 to 2021 were obtained using FluNet. Joinpoint regression was used to describe global influenza virus trends, and clustering analyses were used to classify the ITZs.

RESULTS

The global median average positive rate for total influenza virus was 16.19% (interquartile range: 11.62-25.70%). Overall, three major subtypes (influenza H1, H3, and B viruses) showed alternating epidemics. Notably, the proportion of influenza B viruses increased significantly from July 2020 to June 2021, reaching 62.66%. The primary peaks of influenza virus circulation in the north were earlier than those in the south. Global influenza virus circulation was significantly characterized by seven ITZs, including "Northern America" (primary peak: week 10), "Eastern & Southern-Asia" (primary peak: week 10), "Europe" (primary peak: week 11), "Asia-Europe" (primary peak: week 12), "Southern-America" (primary peak: week 30), "Oceania-Melanesia-Polynesia" (primary peak: week 39), and "Africa" (primary peak: week 46).

CONCLUSION

Global influenza virus circulation was significantly characterized by seven ITZs that could be applied to influenza surveillance and warning.

Spatial, temporal and evolutionary insight into seasonal epidemic Influenza A virus strains near the equatorial line: The case of Ecuador

To study the spatial and temporal patterns of Influenza A virus (IAV) is essential for an efficient control of the disease caused by IAV and efficient vaccination programs. However, spatiotemporal patterns of spread as well as genetic lineage circulation of IAV on a countrywide scale have not been clearly determined for many tropical regions of the world. In order to gain insight into these matters, the spatial and temporal patterns of IAV in six different geographic regions of Ecuador, from 2011 to 2021, were determined and the timing and magnitude of IAV outbreaks in these localities investigated. The results of these studies revealed that although Ecuador is a South American country situated in the Equator line, its IAV epidemiology resembles that of temperate Northern Hemisphere countries. Phylogenetic analysis of H1N1pdm09 and H3N2 IAV strains isolated in five different localities of Ecuador revealed that provinces in the south of this country have the largest effective population size by comparison with provinces in the north, suggesting that the southern provinces may be acting as a source of IAV. Co-circulation of different H1N1pdm09 and H3N2 genetic lineages was observed in different geographic regions of Ecuador.

How heterogeneous is the dengue transmission profile in Brazil? A study in six Brazilian states

Dengue is a vector-borne disease present in most tropical countries, infecting an average of 50 to 100 million people per year. Socioeconomic, demographic, and environmental factors directly influence the transmission cycle of the dengue virus (DENV). In Brazil, these factors vary between regions producing different profiles of dengue transmission and challenging the epidemiological surveillance of the disease. In this article, we aimed at classifying the profiles of dengue transmission in 1,823 Brazilian municipalities, covering different climates, from 2010 to 2019. Time series data of dengue cases were obtained from six states: Ceará and Maranhão in the semiarid Northeast, Minas Gerais in the countryside, Espírito Santo and Rio de Janeiro in the tropical Atlantic coast, and Paraná in the subtropical region. To describe the time series, we proposed a set of epi-features of the magnitude and duration of the dengue epidemic cycles, totaling 13 indicators. Using these epi-features as inputs, a multivariate cluster algorithm was employed to classify the municipalities according to their dengue transmission profile. Municipalities were classified into four distinct dengue transmission profiles: persistent transmission (7.8%), epidemic (21.3%), episodic/epidemic (43.2%), and episodic transmission (27.6%). Different profiles were associated with the municipality’s population size and climate. Municipalities with higher incidence and larger populations tended to be classified as persistent transmission, suggesting the existence of critical community size. This association, however, varies depending on the state, indicating the importance of other factors. The proposed classification is useful for developing more specific and precise surveillance protocols for regions with different dengue transmission profiles, as well as more precise public policies for dengue prevention.

Dengue is one of the fastest-growing vector-borne diseases in the world. Currently, vaccines are experimental and are not very effective, so prevention depends on the control of the mosquito Aedes aegypti. Health promotion campaigns aimed at encouraging people to reduce mosquito breeding sites have limited effect. In addition, the heterogeneity of the territories that have dengue becomes a major challenge for the epidemiological surveillance of the disease. Brazil has a territory of continental size, and single standardized surveillance is not very effective for monitoring this arbovirus. Classifying types of dengue dynamics based on features of the epidemiological cycle in each location has the potential to increase the precision of surveillance and control strategies. In our study, we were able to classify areas according to different dengue transmission profiles, ranging from episodic to persistent transmission. These results can provide tools to guide actions aimed at achieving the World Health Organization’s goals of eliminating neglected tropical diseases in countries that have the virus.

Global patterns of seasonal influenza activity, duration of activity and virus (sub)type circulation from 2010 to 2020

Background

Seasonal influenza viruses undergo unpredictable changes, which may lead to antigenic mismatch between circulating and vaccine strains and to a reduced vaccine effectiveness. A continuously updated knowledge of influenza strain circulation and seasonality is essential to optimize the effectiveness of influenza vaccination campaigns. We described the global epidemiology of influenza between the 2009 A(H1N1)p and the 2020 COVID‐19 pandemic.

Methods

Influenza virological surveillance data were obtained from the WHO‐FluNet database. We determined the median proportion of influenza cases caused by the different influenza virus types, subtypes, and lineages; the typical timing of the epidemic peak; and the median duration of influenza epidemics (applying the annual average percentage method with a 75% threshold).

Results

We included over 4.6 million influenza cases from 149 countries. The median proportion of influenza cases caused by type A viruses was 75.5%, highest in the Southern hemisphere (81.6%) and lowest in the intertropical belt (73.0%), and ranged across seasons between 60.9% in 2017 and 88.7% in 2018. Epidemic peaks typically occurred during winter months in Northern and Southern hemisphere countries, while much more variability emerged in tropical countries. Influenza epidemics lasted a median of 25 weeks (range 8–42) in countries lying between 30°N and 26°S, and a median of 9 weeks (range 5–25) in countries outside this latitude range.

Conclusions

This work will establish an important baseline to better understand factors that influence seasonal influenza dynamics and how COVID‐19 may have affected seasonal activity and influenza virus types, subtypes, and lineages circulation patterns.

Visual Analytic Tools and Techniques in Population Health and Health Services Research: Scoping Review

Background

Visual analytics (VA) promotes the understanding of data with visual, interactive techniques, using analytic and visual engines. The analytic engine includes automated techniques, whereas common visual outputs include flow maps and spatiotemporal hot spots.

Objective

This scoping review aims to address a gap in the literature, with the specific objective to synthesize literature on the use of VA tools, techniques, and frameworks in interrelated health care areas of population health and health services research (HSR).

Methods

Using the 2018 PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, the review focuses on peer-reviewed journal articles and full conference papers from 2005 to March 2019. Two researchers were involved at each step, and another researcher arbitrated disagreements. A comprehensive abstraction platform captured data from diverse bodies of the literature, primarily from the computer and health sciences.

Results

After screening 11,310 articles, findings from 55 articles were synthesized under the major headings of visual and analytic engines, visual presentation characteristics, tools used and their capabilities, application to health care areas, data types and sources, VA frameworks, frameworks used for VA applications, availability and innovation, and co-design initiatives. We found extensive application of VA methods used in areas of epidemiology, surveillance and modeling, health services access, use, and cost analyses. All articles included a distinct analytic and visualization engine, with varying levels of detail provided. Most tools were prototypes, with 5 in use at the time of publication. Seven articles presented methodological frameworks. Toward consistent reporting, we present a checklist, with an expanded definition for VA applications in health care, to assist researchers in sharing research for greater replicability. We summarized the results in a Tableau dashboard.

Conclusions

With the increasing availability and generation of big health care data, VA is a fast-growing method applied to complex health care data. What makes VA innovative is its capability to process multiple, varied data sources to demonstrate trends and patterns for exploratory analysis, leading to knowledge generation and decision support. This is the first review to bridge a critical gap in the literature on VA methods applied to the areas of population health and HSR, which further indicates possible avenues for the adoption of these methods in the future. This review is especially important in the wake of COVID-19 surveillance and response initiatives, where many VA products have taken center stage.

International Registered Report Identifier (IRRID)

RR2-10.2196/14019

Computational Forecasting Methodology for Acute Respiratory Infectious Disease Dynamics

The study of infectious disease behavior has been a scientific concern for many years as early identification of outbreaks provides great advantages including timely implementation of public health measures to limit the spread of an epidemic. We propose a methodology that merges the predictions of (i) a computational model with machine learning, (ii) a projection model, and (iii) a proposed smoothed endemic channel calculation. The predictions are made on weekly acute respiratory infection (ARI) data obtained from epidemiological reports in Mexico, along with the usage of key terms in the Google search engine. The results obtained with this methodology were compared with state-of-the-art techniques resulting in reduced root mean squared percentage error (RMPSE) and maximum absolute percent error (MAPE) metrics, achieving a MAPE of 21.7%. This methodology could be extended to detect and raise alerts on possible outbreaks on ARI as well as for other seasonal infectious diseases.

Dengue spatiotemporal dynamics in the Federal District, Brazil: occurrence and permanence of epidemics

The specific characteristics of the Federal District (DF) favor the introduction, reproduction, dissemination, and permanence of dengue vector and viruses. Here, we aimed to analyze the spatiotemporal patterns of dengue epidemics in the Administrative Regions (RAs) of the DF from January 2007 to December 2017. We used Fourier partial series model to obtain a seasonal signature of the time series, which allowed calculating indicators of permanence (number of epidemic years, number of epidemic months per year, the proportion of epidemic months for the period) and time/moment of epidemics (month of epidemic peak). A total of 82 epidemics were recorded in this period. The RAs with the largest number of epidemic years were Varjão (5 epidemics), Gama, Lago Sul, and Sobradinho (4 epidemics). These last three RAs also had the highest proportions of epidemic months of the entire study period (9 epidemic months). The RAs with urban centrality function had an earlier epidemic peak than the others, in February and March. Epidemics showed high permanence values in RAs with different types of occupations, emphasizing the need to consider the social organization of space processes in dengue distribution studies.

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.

The epidemiological signature of influenza B virus and its B/Victoria and B/Yamagata lineages in the 21st century

We describe the epidemiological characteristics, pattern of circulation, and geographical distribution of influenza B viruses and its lineages using data from the Global Influenza B Study. We included over 1.8 million influenza cases occurred in thirty-one countries during 2000–2018. We calculated the proportion of cases caused by influenza B and its lineages; determined the timing of influenza A and B epidemics; compared the age distribution of B/Victoria and B/Yamagata cases; and evaluated the frequency of lineage-level mismatch for the trivalent vaccine. The median proportion of influenza cases caused by influenza B virus was 23.4%, with a tendency (borderline statistical significance, p = 0.060) to be higher in tropical vs. temperate countries. Influenza B was the dominant virus type in about one every seven seasons. In temperate countries, influenza B epidemics occurred on average three weeks later than influenza A epidemics; no consistent pattern emerged in the tropics. The two B lineages caused a comparable proportion of influenza B cases globally, however the B/Yamagata was more frequent in temperate countries, and the B/Victoria in the tropics (p = 0.048). B/Yamagata patients were significantly older than B/Victoria patients in almost all countries. A lineage-level vaccine mismatch was observed in over 40% of seasons in temperate countries and in 30% of seasons in the tropics. The type B virus caused a substantial proportion of influenza infections globally in the 21^st century, and its two virus lineages differed in terms of age and geographical distribution of patients. These findings will help inform health policy decisions aiming to reduce disease burden associated with seasonal influenza.

Comparison of malaria incidence rates and socioeconomic-environmental factors between the states of Acre and Rondônia: a spatio-temporal modelling study

BACKGROUND

Plasmodium falciparum malaria is a threat to public health, but Plasmodium vivax malaria is most prevalent in Latin America, where the incidence rate has been increasing since 2016, particularly in Venezuela and Brazil. The Brazilian Amazon reported 193,000 cases in 2017, which were mostly confirmed as P. vivax (~ 90%). Herein, the relationships among malaria incidence rates and the proportion of accumulated deforestation were contrasted using data from the states of Acre and Rondônia in the south-western Brazilian Amazon. The main purpose is to test the hypothesis that the observed difference in incidence rates is associated with the proportion of accumulated deforestation.

METHODS

An ecological study using spatial and temporal models for mapping and modelling malaria risk was performed. The municipalities of Acre and Rondônia were the spatial units of analysis, whereas month and year were the temporal units. The number of reported malaria cases from 2009 until 2015 were used to calculate the incidence rate per 1000 people at risk. Accumulated deforestation was calculated using publicly available satellite images. Geographically weighted regression was applied to provide a local model of the spatial heterogeneity of incidence rates. Time-series dynamic regression was applied to test the correlation of incidence rates and accumulated deforestation, adjusted by climate and socioeconomic factors.

RESULTS

The malaria incidence rate declined in Rondônia but remained stable in Acre. There was a high and positive correlation between the decline in malaria and higher proportions of accumulated deforestation in Rondônia. Geographically weighted regression showed a complex relationship. As deforestation increased, malaria incidence also increased in Acre, while as deforestation increased, malaria incidence decreased in Rondônia. Time-series dynamic regression showed a positive association between malaria incidence and precipitation and accumulated deforestation, whereas the association was negative with the human development index in the westernmost areas of Acre.

CONCLUSION

Landscape modification caused by accumulated deforestation is an important driver of malaria incidence in the Brazilian Amazon. However, this relationship is not linearly correlated because it depends on the overall proportion of the land covered by forest. For regions that are partially degraded, forest cover becomes a less representative component in the landscape, causing the abovementioned non-linear relationship. In such a scenario, accumulated deforestation can lead to a decline in malaria incidence.

Epidemiology and timing of seasonal influenza epidemics in the Asia-Pacific region, 2010-2017: implications for influenza vaccination programs

Background

Description of the epidemiology of influenza is needed to inform influenza vaccination policy. Here we examined influenza virus circulation in countries in the Asia-Pacific region and compared the timing of seasonal epidemics with the timing of influenza vaccination.

Methods

Data were obtained from the World Health Organization (WHO) FluNet database for 2010–2017 for countries in the WHO Asia-Pacific region. Data from countries covering ≥5 consecutive seasons and ≥ 100 influenza positive cases per year were included. Median proportions of cases for each influenza virus type were calculated by country and season. The timing and amplitude of the epidemic peaks were determined by Fourier decomposition. Vaccination timing was considered appropriate for each country if it was recommended ≤4 months before the primary peak of influenza circulation.

Results

Seven hundred eleven thousand seven hundred thirty-four influenza cases were included from 19 countries. Peak circulation coincided with the winter seasons in most countries, although patterns were less clear in some countries in the inter-tropical area due to substantial secondary peaks. Influenza A/H3N2 dominated overall, but proportions of A and B strains varied by year and by country. Influenza B represented 31.4% of all cases. The WHO-recommended timing for influenza vaccination was appropriate in 12 countries. Vaccination timing recommendations were considered inappropriate in Laos, Cambodia, and Thailand, and were inconclusive for India, Sri Lanka, Singapore, and Vietnam due to unclear seasonality of influenza virus circulation.

Conclusions

Influenza virus circulation varied considerably across the Asia-Pacific region with an unusually high burden of influenza B. The recommended timing for vaccination was appropriate in most countries, except for several countries with unclear seasonality, mainly located in the inter-tropical area.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-6647-y) contains supplementary material, which is available to authorized users.

Fogarty International Center collaborative networks in infectious disease modeling: Lessons learnt in research and capacity building

Due to a combination of ecological, political, and demographic factors, the emergence of novel pathogens has been increasingly observed in animals and humans in recent decades. Enhancing global capacity to study and interpret infectious disease surveillance data, and to develop data-driven computational models to guide policy, represents one of the most cost-effective, and yet overlooked, ways to prepare for the next pandemic. Epidemiological and behavioral data from recent pandemics and historic scourges have provided rich opportunities for validation of computational models, while new sequencing technologies and the 'big data' revolution present new tools for studying the epidemiology of outbreaks in real time. For the past two decades, the Division of International Epidemiology and Population Studies (DIEPS) of the NIH Fogarty International Center has spearheaded two synergistic programs to better understand and devise control strategies for global infectious disease threats. The Multinational Influenza Seasonal Mortality Study (MISMS) has strengthened global capacity to study the epidemiology and evolutionary dynamics of influenza viruses in 80 countries by organizing international research activities and training workshops. The Research and Policy in Infectious Disease Dynamics (RAPIDD) program and its precursor activities has established a network of global experts in infectious disease modeling operating at the research-policy interface, with collaborators in 78 countries. These activities have provided evidence-based recommendations for disease control, including during large-scale outbreaks of pandemic influenza, Ebola and Zika virus. Together, these programs have coordinated international collaborative networks to advance the study of emerging disease threats and the field of computational epidemic modeling. A global community of researchers and policy-makers have used the tools and trainings developed by these programs to interpret infectious disease patterns in their countries, understand modeling concepts, and inform control policies. Here we reflect on the scientific achievements and lessons learnt from these programs (h-index = 106 for RAPIDD and 79 for MISMS), including the identification of outstanding researchers and fellows; funding flexibility for timely research workshops and working groups (particularly relative to more traditional investigator-based grant programs); emphasis on group activities such as large-scale modeling reviews, model comparisons, forecasting challenges and special journal issues; strong quality control with a light touch on outputs; and prominence of training, data-sharing, and joint publications.

The 1918 influenza pandemic in Montevideo: The southernmost capital city in the Americas

BACKGROUND

Few studies have addressed the impact and dynamics of the 1918-1919 influenza pandemic in temperate regions of South America.

OBJECTIVE

To identify key factors for influenza onset, spread, and mortality in Montevideo and Uruguay in 1918-1919.

METHODS

An analysis of official national records of the public health system of Uruguay was performed.

RESULTS

From November to December of 1918 (spring), a total of 131 deaths due to influenza occurred in Montevideo and a total of 296 deaths accounted from July to September of 1919 (winter) in the same city. The total deaths attributed to influenza in Uruguay in 1918 and 1919 were 926 and 1089, respectively. In contrast, the mean annual mortality attributed to influenza in Uruguay from 1908 to 1917 was 50.9. A pattern of age-shift in mortality in the two pandemic waves studied was observed.

CONCLUSIONS

The results of studies revealed that Montevideo was first hit by the devastating second wave of the pandemic of 1918, arriving Montevideo at the end of the spring of that year. The third wave arrived by July 1919, in the winter season, and in the capital city was as severe as the second one.

Epidemiology of seasonal influenza in the Middle East and North Africa regions, 2010-2016: Circulating influenza A and B viruses and spatial timing of epidemics

BACKGROUND

There is a limited knowledge regarding the epidemiology of influenza in Middle East and North Africa.

OBJECTIVES

We described the patterns of influenza circulation and the timing of seasonal epidemics in countries of Middle East and North Africa.

METHODS

We used virological surveillance data for 2010-2016 from the WHO FluNet database. In each country, we calculated the median proportion of cases that were caused by each virus type and subtype; determined the timing and amplitude of the primary and secondary peaks; and used linear regression models to test for spatial trends in the timing of epidemics.

RESULTS

We included 70 532 influenza cases from seventeen countries. Influenza A and B accounted for a median 76.5% and 23.5% of cases in a season and were the dominant type in 86.8% and 13.2% of seasons. The proportion of influenza A cases that were subtyped was 85.9%, while only 4.4% of influenza B cases were characterized. For most countries, influenza seasonality was similar to the Northern Hemisphere, with a single large peak between January and March; exceptions were the countries in the Arabian Peninsula and Jordan, all of which showed clear secondary peaks, and some countries had an earlier primary peak (in November-December in Bahrain and Qatar). The direction of the timing of influenza activity was east to west and south to north in 2012-2013 and 2015-2016, and west to east in 2014-2015.

CONCLUSIONS

The epidemiology of influenza is generally uniform in countries of Middle East and North Africa, with influenza B playing an important role in the seasonal disease burden.

Search engines, news wires and digital epidemiology: Presumptions and facts

BACKGROUND

Digital epidemiology tries to identify diseases dynamics and spread behaviors using digital traces collected via search engines logs and social media posts. However, the impacts of news on information-seeking behaviors have been remained unknown.

METHODS

Data employed in this research provided from two sources, (1) Parsijoo search engine query logs of 48 months, and (2) a set of documents of 28 months of Parsijoo's news service. Two classes of topics, i.e. macro-topics and micro-topics were selected to be tracked in query logs and news. Keywords of the macro-topics were automatically generated using web provided resources and exceeded 10k. Keyword set of micro-topics were limited to a numerable list including terms related to diseases and health-related activities. The tests are established in the form of three studies. Study A includes temporal analyses of 7 macro-topics in query logs. Study B considers analyzing seasonality of searching patterns of 9 micro-topics, and Study C assesses the impact of news media coverage on users' health-related information-seeking behaviors.

RESULTS

Study A showed that the hourly distribution of various macro-topics followed the changes in social activity level. Conversely, the interestingness of macro-topics did not follow the regulation of topic distributions. Among macro-topics, "Pharmacotherapy" has highest interestingness level and wider time-window of popularity. In Study B, seasonality of a limited number of diseases and health-related activities were analyzed. Trends of infectious diseases, such as flu, mumps and chicken pox were seasonal. Due to seasonality of most of diseases covered in national vaccination plans, the trend belonging to "Immunization and Vaccination" was seasonal, as well. Cancer awareness events caused peaks in search trends of "Cancer" and "Screening" micro-topics in specific days of each year that mimic repeated patterns which may mistakenly be identified as seasonality. In study C, we assessed the co-integration and correlation between news and query trends. Our results demonstrated that micro-topics sparsely covered in news media had lowest level of impressiveness and, subsequently, the lowest impact on users' intents.

CONCLUSION

Our results can reveal public reaction to social events, diseases and prevention procedures. Furthermore, we found that news trends are co-integrated with search queries and are able to reveal health-related events; however, they cannot be used interchangeably. It is recommended that the user-generated contents and news documents are analyzed mutually and interactively.

The spatiotemporal characteristics of influenza A and B in the WHO European Region: can one define influenza transmission zones in Europe?

We aimed to assess the epidemiology and spatiotemporal patterns of influenza in the World Health Organization (WHO) European Region and evaluate the validity of partitioning the Region into five influenza transmission zones (ITZs) as proposed by the WHO. We used the FluNet database and included over 650,000 influenza cases from 2000 to 2015. We analysed the data by country and season (from July to the following June). We calculated the median proportion of cases caused by each virus type in a season, compared the timing of the primary peak between countries and used a range of cluster analysis methods to assess the degree of overlap between the WHO-defined and data-driven ITZs. Influenza A and B caused, respectively, a median of 83% and 17% cases in a season. There was a significant west-to-east and non-significant (p = 0.10) south-to-north gradient in the timing of influenza activity. Typically, influenza peaked in February and March; influenza A earlier than influenza B. Most countries in the WHO European Region would fit into two ITZs: ‘Western Europe’ and ‘Eastern Europe’; countries bordering Asia may be better placed into extra-European ITZs. Our findings have implications for the presentation of surveillance data and prevention and control measures in this large WHO Region.

Dengue hospitalisations in Brazil: annual wave from West to East and recent increase among children

The number of dengue epidemics in Brazil has increased dramatically in the last 15 years. In this study, we analysed the seasonal patterns in the incidence of hospitalisations due to dengue across the different states of Brazil and compared these with the corresponding climatic patterns. We discovered that the seasonality of dengue hospitalisations in Brazil has a clear zonal gradient, characterised by the progression of primary peaks from West to East during the first half of the year, which may be associated with the increased vapour pressure and rainfall during this period, leading to increased mosquito abundance and activity. We also found that the proportion of children among hospitalised individuals was especially high during the peak outbreaks in 2007/2008 and 2010. This may be due to the emergence and spread of the new DENV-2 Southeast Asian genotype lineage II from 2007, which has probably arrived from the Caribbean and may have caused an increase in incidence and severity of the disease, particularly among children. Our findings may allow health systems to improve control interventions and contribute to reducing dengue morbidity and mortality by using integrated vector control in conjunction with early diagnosis and prompt supportive care.

Rotavirus vaccination takes seasonal signature of childhood diarrhea back to pre-sanitation era in Brazil

OBJECTIVES

This study aimed to examine the previously unknown long-term spatio-temporal patterns in diarrheal morbidity and mortality across age groups and geography in Brazil under the light of evolving socioeconomic factors and interventions.

METHODS

Nationwide mortality (1979-2014) and hospitalization (1998-2014) data were obtained from the Brazilian Ministry of Health. Analyses of long-term secular trends and seasonality of diarrheal morbidity and mortality were performed in EPIPOI (www.epipoi.info).

RESULTS

For most states, the primary peak in mortality risk among children under 5 years occurred from December-April (summer/early autumn) from 1979-1988. From 2000-2005 (before the 2006 implementation of rotavirus vaccination), the pattern switched to June-October (winter/early spring). By 2007-2014, the peak in mortality shifted back towards summer/early autumn. A similar pattern was observed for hospitalizations. These patterns were particularly apparent in non-equatorial regions of the country. In contrast, the risk of diarrhea-related death among older children (5-19 years) did not demonstrate well-defined seasonality or spatial patterns.

CONCLUSIONS

Rotavirus vaccination policies were associated with a shift in the timing of seasonal peaks in children under 5, reminiscent of the summer diarrhea period common decades prior. Additionally, young children were shown to have distinct disease patterns compared to other age groups, suggesting different etiologies.

Influenza seasonality goes south in the Yucatan Peninsula: The case for a different influenza vaccine calendar in this Mexican region

INTRODUCTION

While vaccination may be relatively straightforward for regions with a well-defined winter season, the situation is quite different for tropical regions. Influenza activity in tropical regions might be out of phase with the dynamics predicted for their hemispheric group thereby impacting the effectiveness of the immunization campaign.

OBJECTIVE

To investigate how the climatic diversity of Mexico hinders its existing influenza immunization strategy and to suggest that the hemispheric vaccine recommendations be tailored to the regional level in order to optimize vaccine effectiveness.

METHODS

We studied the seasonality of influenza throughoutMexico by modeling virological and mortality data.De-trended time series of each Mexican state were analyzed by Fourier decomposition to describe the amplitude and timing of annual influenza epidemic cycles and to compare with each the timing of the WHO's Northern and Southern Hemispheric vaccination schedule.

FINDINGS

The timings of the primary (major) peaks of both virological and mortality data for most Mexican states are well aligned with the Northern Hemisphere winter (December-February) and vaccine schedule. However, influenza peaks in September in the three states of the Yucatan Peninsula. Influenza-related mortality also peaks in September in Quintana Roo and Yucatan whereas it peaks in May in Campeche. As the current timing of vaccination in Mexico is between October and November, more than half of the annual influenza cases have already occurred in the Yucatan Peninsula states by the time the Northern Hemispheric vaccine is delivered and administered.

CONCLUSION

The current Northern Hemispheric influenza calendar adopted for Mexico is not optimal for the Yucatan Peninsula states thereby likely reducing the effectiveness of the immunization of the population. We recommend that Mexico tailor its immunization strategy to better reflect its climatologic and epidemiological diversity and adopt the WHO Southern Hemisphere influenza vaccine and schedule for the Yucatan Peninsula.

Spatial-temporal diffusion of dengue in the municipality of Rio de Janeiro, Brazil, 2000-2013

The city of Rio de Janeiro, Brazil, shows high potential receptiveness to the introduction, dissemination, and persistence of dengue transmission. The pattern of territorial occupation in the municipality produced a heterogeneous and diverse mosaic, with differential vector distribution between and within neighborhoods, producing distinct epidemics on this scale of observation. The study seeks to identify these epidemics and the pattern of spatial and temporal diffusion of dengue transmission. A model was used for the identification of epidemics, considering the epidemic peak years and months, spatial distribution, and permanence of epidemics from January 2000 to December 2013. A total of 495 epidemic peaks were counted, and the time scale showed the highest occurrence in the months of March, April, and February, respectively. Some neighborhoods appear to present persistent dengue incidence, and the pattern of diffusion allows identifying key trajectories and timely months for intervention.

Characteristics of seasonal influenza A and B in Latin America: Influenza surveillance data from ten countries

Introduction

The increased availability of influenza surveillance data in recent years justifies an actual and more complete overview of influenza epidemiology in Latin America. We compared the influenza surveillance systems and assessed the epidemiology of influenza A and B, including the spatio-temporal patterns of influenza epidemics, in ten countries and sub-national regions in Latin America.

Methods

We aggregated the data by year and country and characteristics of eighty-two years were analysed. We calculated the median proportion of laboratory-confirmed influenza cases caused by each virus strain, and compared the timing and amplitude of the primary and secondary peaks between countries.

Results

37,087 influenza cases were reported during 2004–2012. Influenza A and B accounted for a median of 79% and, respectively, 21% of cases in a year. The percentage of influenza A cases that were subtyped was 82.5%; for influenza B, 15.6% of cases were characterized. Influenza A and B were dominant in seventy-five (91%) and seven (9%) years, respectively. In half (51%) of the influenza A years, influenza A(H3N2) was dominant, followed by influenza A(H1N1)pdm2009 (41%) and pre-pandemic A(H1N1) (8%). The primary peak of influenza activity was in June-September in temperate climate countries, with little or no secondary peak. Tropical climate countries had smaller primary peaks taking place in different months and frequently detectable secondary peaks.

Conclusions

We found that good influenza surveillance data exists in Latin America, although improvements can still be made (e.g. a better characterization of influenza B specimens); that influenza B plays a considerable role in the seasonal influenza burden; and that there is substantial heterogeneity of spatio-temporal patterns of influenza epidemics. To improve the effectiveness of influenza control measures in Latin America, tropical climate countries may need to develop innovative prevention strategies specifically tailored to the spatio-temporal patterns of influenza in this region.

Respiratory syncytial virus seasonality in Brazil: implications for the immunisation policy for at-risk populations

Respiratory syncytial virus (RSV) infection is the leading cause of hospitalisation for respiratory diseases among children under 5 years old. The aim of this study was to analyse RSV seasonality in the five distinct regions of Brazil using time series analysis (wavelet and Fourier series) of the following indicators: monthly positivity of the immunofluorescence reaction for RSV identified by virologic surveillance system, and rate of hospitalisations per bronchiolitis and pneumonia due to RSV in children under 5 years old (codes CID-10 J12.1, J20.5, J21.0 and J21.9). A total of 12,501 samples with 11.6% positivity for RSV (95% confidence interval 11 - 12.2), varying between 7.1 and 21.4% in the five Brazilian regions, was analysed. A strong trend for annual cycles with a stable stationary pattern in the five regions was identified through wavelet analysis of the indicators. The timing of RSV activity by Fourier analysis was similar between the two indicators analysed and showed regional differences. This study reinforces the importance of adjusting the immunisation period for high risk population with the monoclonal antibody palivizumab taking into account regional differences in seasonality of RSV.

Temporal Patterns of Influenza A and B in Tropical and Temperate Countries: What Are the Lessons for Influenza Vaccination?

Introduction

Determining the optimal time to vaccinate is important for influenza vaccination programmes. Here, we assessed the temporal characteristics of influenza epidemics in the Northern and Southern hemispheres and in the tropics, and discuss their implications for vaccination programmes.

Methods

This was a retrospective analysis of surveillance data between 2000 and 2014 from the Global Influenza B Study database. The seasonal peak of influenza was defined as the week with the most reported cases (overall, A, and B) in the season. The duration of seasonal activity was assessed using the maximum proportion of influenza cases during three consecutive months and the minimum number of months with ≥80% of cases in the season. We also assessed whether co-circulation of A and B virus types affected the duration of influenza epidemics.

Results

212 influenza seasons and 571,907 cases were included from 30 countries. In tropical countries, the seasonal influenza activity lasted longer and the peaks of influenza A and B coincided less frequently than in temperate countries. Temporal characteristics of influenza epidemics were heterogeneous in the tropics, with distinct seasonal epidemics observed only in some countries. Seasons with co-circulation of influenza A and B were longer than influenza A seasons, especially in the tropics.

Discussion

Our findings show that influenza seasonality is less well defined in the tropics than in temperate regions. This has important implications for vaccination programmes in these countries. High-quality influenza surveillance systems are needed in the tropics to enable decisions about when to vaccinate.

Unintended Pregnancies in Brazil - A Challenge for the Recommendation to Delay Pregnancy Due to Zika

Because of the potential link between the ongoing Zika virus outbreak and a surge in the number of cases of congenital microcephaly, officials in Latin America have recommended that women postpone pregnancy until this association is firmly established or the outbreak subsides. However, in all these countries a large proportion of babies are still born out of unplanned pregnancies. Teenage girls are particularly at high risk, as they often lack access to preventive contraception methods, or the knowledge to use them appropriately. To gauge the magnitude of the barriers preventing the implementation of such a recommendation in Brazil, the country so far most affected by the Zika epidemic, we evaluated pregnancy rates in teenage girls, and their spatial heterogeneity in the country, in recent years (2012-2014). Nearly 20% of children born in Brazil today (~560,000 live births) are by teenage mothers. Birth incidence is far higher in the tropical and poorer northern states. However, in absolute terms most births occur in the populous southeastern states, matching to a large extent the geographic distribution of dengue (an indicator of suitable climatic and sociodemographic conditions for the circulation of Aedes mosquitoes). These findings indicate that recommendation to delay pregnancy will leave over half a million pregnant adolescents in Brazil vulnerable to infection every year if not accompanied by effective education and real access to prevention.

Influenza seasonality in Madagascar: the mysterious African free-runner

BACKGROUND

The seasonal drivers of influenza activity remain debated in tropical settings where epidemics are not clearly phased. Antananarivo is a particularly interesting case study because it is in Madagascar, an island situated in the tropics and with quantifiable connectivity levels to other countries.

OBJECTIVES

We aimed at disentangling the role of environmental forcing and population fluxes on influenza seasonality in Madagascar.

METHODS

We compiled weekly counts of laboratory-confirmed influenza-positive specimens for the period 2002 to 2012 collected in Antananarivo, with data available from sub-Saharan countries and countries contributing most foreign travelers to Madagascar. Daily climate indicators were compiled for the study period.

RESULTS

Overall, influenza activity detected in Antananarivo predated that identified in temperate Northern Hemisphere locations. This activity presented poor temporal matching with viral activity in other countries from the African continent or countries highly connected to Madagascar excepted for A(H1N1)pdm09. Influenza detection in Antananarivo was not associated with travel activity and, although it was positively correlated with all climatic variables studied, such association was weak.

CONCLUSIONS

The timing of influenza activity in Antananarivo is irregular, is not driven by climate, and does not align with that of countries in geographic proximity or highly connected to Madagascar. This work opens fresh questions regarding the drivers of influenza seasonality globally particularly in mid-latitude and less-connected regions to tailor vaccine strategies locally.

A global map of hemispheric influenza vaccine recommendations based on local patterns of viral circulation

Both the Northern and the Southern Hemisphere annual WHO influenza vaccine recommendations are designed to ensure vaccine delivery before the winter-time peak of viral circulation in each hemisphere. However, influenza seasonal patterns are highly diverse in tropical countries and may be out of phase with the WHO recommendations for their respective hemisphere. We modelled the peak timing of influenza activity for 125 countries using laboratory-based surveillance data from the WHO's FLUNET database and compared it with the influenza hemispheric recommendations in place. Influenza vaccine recommendations for respectively 25% and 39% of the Northern and Southern Hemisphere countries were out of phase with peak influenza circulation in their corresponding hemisphere (62% and 53%, respectively, when the analysis was limited to the 52 countries in the tropical belt). These results indicate that routine influenza immunization efforts should be closely tailored to local patterns of viral circulation, rather than a country's hemispheric position.

Seasonal drivers of the epidemiology of arthropod-borne viruses in Australia

Arthropod-borne viruses are a major cause of emerging disease with significant public health and economic impacts. However, the factors that determine their activity and seasonality are not well understood. In Australia, a network of sentinel cattle herds is used to monitor the distribution of several such viruses and to define virus-free regions. Herein, we utilize these serological data to describe the seasonality, and its drivers, of three economically important animal arboviruses: bluetongue virus, Akabane virus and bovine ephemeral fever virus. Through epidemiological time-series analyses of sero-surveillance data of 180 sentinel herds between 2004–2012, we compared seasonal parameters across latitudes, ranging from the tropical north (−10°S) to the more temperate south (−40°S). This analysis revealed marked differences in seasonality between distinct geographic regions and climates: seasonality was most pronounced in southern regions and gradually decreased as latitude decreased toward the Equator. Further, we show that both the timing of epidemics and the average number of seroconversions have a strong geographical component, which likely reflect patterns of vector abundance through co-varying climatic factors, especially temperature and rainfall. Notably, despite their differences in biology, including insect vector species, all three viruses exhibited very similar seasonality. By revealing the factors that shape spatial and temporal distributions, our study provides a more complete understanding of arbovirus seasonality that will enable better risk predictions.

Arthropod-borne viruses (arboviruses) are a group of viruses that can have major impacts on public health, animal health and agricultural trade, and appear to be increasing in both number and prevalence worldwide. Despite their importance as emerging pathogens, the spatial patterns, long-term seasonal characteristics and drivers of seasonality in many arboviruses are poorly understood. The island continent of Australia provides an ideal case study for the spatial analysis of emerging arboviruses, harboring diverse climatic conditions across a wide range of latitudes. Herein we utilize long-term serological data from a nationwide network of sentinel herds in Australia to describe the seasonality of three economically important animal arboviruses: bluetongue virus, Akabane virus and bovine ephemeral fever virus. Using epidemiological time series analysis, we demonstrate that these viruses exhibit a distinct spatial pattern in both the peak timing and intensity of annual epidemic cycles, with the strongest seasonality observed in southerly geographic regions. In addition, we reveal the climatic factors that drive patterns of arbovirus distribution and, by doing so, provide a more complete understanding of arbovirus seasonality, which in turn will improve the risk assessment of these viruses.

Visualization and analytics tools for infectious disease epidemiology: a systematic review

BACKGROUND

A myriad of new tools and algorithms have been developed to help public health professionals analyze and visualize the complex data used in infectious disease control. To better understand approaches to meet these users' information needs, we conducted a systematic literature review focused on the landscape of infectious disease visualization tools for public health professionals, with a special emphasis on geographic information systems (GIS), molecular epidemiology, and social network analysis. The objectives of this review are to: (1) identify public health user needs and preferences for infectious disease information visualization tools; (2) identify existing infectious disease information visualization tools and characterize their architecture and features; (3) identify commonalities among approaches applied to different data types; and (4) describe tool usability evaluation efforts and barriers to the adoption of such tools.

METHODS

We identified articles published in English from January 1, 1980 to June 30, 2013 from five bibliographic databases. Articles with a primary focus on infectious disease visualization tools, needs of public health users, or usability of information visualizations were included in the review.

RESULTS

A total of 88 articles met our inclusion criteria. Users were found to have diverse needs, preferences and uses for infectious disease visualization tools, and the existing tools are correspondingly diverse. The architecture of the tools was inconsistently described, and few tools in the review discussed the incorporation of usability studies or plans for dissemination. Many studies identified concerns regarding data sharing, confidentiality and quality. Existing tools offer a range of features and functions that allow users to explore, analyze, and visualize their data, but the tools are often for siloed applications. Commonly cited barriers to widespread adoption included lack of organizational support, access issues, and misconceptions about tool use.

DISCUSSION AND CONCLUSION

As the volume and complexity of infectious disease data increases, public health professionals must synthesize highly disparate data to facilitate communication with the public and inform decisions regarding measures to protect the public's health. Our review identified several themes: consideration of users' needs, preferences, and computer literacy; integration of tools into routine workflow; complications associated with understanding and use of visualizations; and the role of user trust and organizational support in the adoption of these tools. Interoperability also emerged as a prominent theme, highlighting challenges associated with the increasingly collaborative and interdisciplinary nature of infectious disease control and prevention. Future work should address methods for representing uncertainty and missing data to avoid misleading users as well as strategies to minimize cognitive overload.

Human parainfluenza virus in patients with influenza-like illness from Central and South America during 2006-2010

Background

Human parainfluenza viruses (HPIVs) are common viral causes of community-acquired pneumonia, particularly in children. The four types of HPIV have world-wide distribution; however, limited information exists about the epidemiological profile of HPIV in Latin-America.

Objective

Provide epidemiologic and phylogenetic information about HPIVs that circulated in Latin America between 2006 and 2010 to better characterize the extent and variability of this respiratory virus in the region.

Methods

Oropharyngeal swabs, demographic data and clinical characteristics were obtained from individuals with influenza-like illness in 10 Latin-American countries between 2006–2010. Specimens were analyzed with culture and molecular methods.

Results

A total of 30 561 individuals were enrolled; 991 (3·2%) were HPIV positive. Most infected participants were male (53·7%) and under 5 years of age (68·7%). The HPIV type most frequently isolated was HPIV-3 (403, 40·7%). In 66/2007 (3·3%) hospitalized individuals, HPIV was identified. The most frequent symptoms at enrollment were cough and rhinorrhea. We identified certain patterns for HPIV-1, -2 and -3 in specific cities. Phylogenetic analysis revealed a homogeneous distribution in the region.

Conclusions

In the current scenario, no vaccine or treatment is available for this pathogen. Our results contribute to the scarce epidemiologic and phylogenetic information of HPIV in the region that could support the development of specific management.

Characterization of regional influenza seasonality patterns in China and implications for vaccination strategies: spatio-temporal modeling of surveillance data

BACKGROUND

The complexity of influenza seasonal patterns in the inter-tropical zone impedes the establishment of effective routine immunization programs. China is a climatologically and economically diverse country, which has yet to establish a national influenza vaccination program. Here we characterize the diversity of influenza seasonality in China and make recommendations to guide future vaccination programs.

METHODS AND FINDINGS

We compiled weekly reports of laboratory-confirmed influenza A and B infections from sentinel hospitals in cities representing 30 Chinese provinces, 2005-2011, and data on population demographics, mobility patterns, socio-economic, and climate factors. We applied linear regression models with harmonic terms to estimate influenza seasonal characteristics, including the amplitude of annual and semi-annual periodicities, their ratio, and peak timing. Hierarchical Bayesian modeling and hierarchical clustering were used to identify predictors of influenza seasonal characteristics and define epidemiologically-relevant regions. The annual periodicity of influenza A epidemics increased with latitude (mean amplitude of annual cycle standardized by mean incidence, 140% [95% CI 128%-151%] in the north versus 37% [95% CI 27%-47%] in the south, p<0.0001). Epidemics peaked in January-February in Northern China (latitude ≥33°N) and April-June in southernmost regions (latitude <27°N). Provinces at intermediate latitudes experienced dominant semi-annual influenza A periodicity with peaks in January-February and June-August (periodicity ratio >0.6 in provinces located within 27.4°N-31.3°N, slope of latitudinal gradient with latitude -0.016 [95% CI -0.025 to -0.008], p<0.001). In contrast, influenza B activity predominated in colder months throughout most of China. Climate factors were the strongest predictors of influenza seasonality, including minimum temperature, hours of sunshine, and maximum rainfall. Our main study limitations include a short surveillance period and sparse influenza sampling in some of the southern provinces.

CONCLUSIONS

Regional-specific influenza vaccination strategies would be optimal in China; in particular, annual campaigns should be initiated 4-6 months apart in Northern and Southern China. Influenza surveillance should be strengthened in mid-latitude provinces, given the complexity of seasonal patterns in this region. More broadly, our findings are consistent with the role of climatic factors on influenza transmission dynamics. Please see later in the article for the Editors' Summary.

Global seasonality of rotavirus disease

BACKGROUND

A substantial number of surveillance studies have documented rotavirus prevalence among children admitted for dehydrating diarrhea. We sought to establish global seasonal patterns of rotavirus disease before the introduction of widespread vaccination.

METHODS

We reviewed studies of rotavirus detection in children with diarrhea published since 1995. We assessed potential relationships between seasonal prevalence and locality by plotting the average monthly proportion of diarrhea cases positive for rotavirus according to geography, country development and latitude. We used linear regression to identify variables that were potentially associated with the seasonal intensity of rotavirus.

RESULTS

Among a total of 99 studies representing all 6 geographic regions of the world, patterns of year-round disease were more evident in low- and low-middle income countries compared with upper-middle and high-income countries where disease was more likely to be seasonal. The level of country development was a stronger predictor of strength of seasonality (P = 0.001) than geographic location or climate. However, the observation of distinctly different seasonal patterns of rotavirus disease in some countries with similar geographic location, climate and level of development indicate that a single unifying explanation for variation in seasonality of rotavirus disease is unlikely.

CONCLUSION

While no unifying explanation emerged for varying rotavirus seasonality globally, the country income level was somewhat more predictive of the likelihood of having seasonal disease than other factors. Future evaluation of the effect of rotavirus vaccination on seasonal patterns of disease in different settings may help understand factors that drive the global seasonality of rotavirus disease.