This two-part article examines the global public health (GPH) information system deficits emerging in the coronavirus disease 2019 (COVID-19) pandemic. It surveys past, missed opportunities for public health (PH) information system and operational improvements, examines current megatrend changes to information management, and describes a new multi-disciplinary model for population-based management (PBM) supported by a GPH Database applicable to pandemics and GPH crises.

The epidemiology of H5N1 and H7N9 avian viruses of humans infected in China differs despite both viruses being avian reassortants that have inherited six internal genes from a common ancestor, H9N2. The median age of infected populations is substantially younger for H5N1 virus (26 years) compared with H7N9 virus (63 years). Population susceptibility to infection with seasonal influenza is understood to be influenced by cross-reactive CD8+ T cells directed towards immunogenic peptides derived from internal viral proteins which may provide some level of protection against further influenza infection. Prior exposure to seasonal influenza peptides may influence the age-related infection patterns observed for H5N1 and H7N9 viruses. A comparison of relatedness of immunogenic peptides between historical human strains and the two avian emerged viruses was undertaken for a possible explanation in the differences in age incidence observed. There appeared to be some relationship between past exposure to related peptides and the lower number of H5N1 virus cases in older populations, however the relationship between prior exposure and older populations among H7N9 virus patients was less clear.

Significant increases in excess all-cause mortality, particularly in the elderly, were observed during the winter of 2014/15 in England. With influenza A(H3N2) the dominant circulating influenza A subtype, this paper determines the contribution of influenza to this excess controlling for weather. A standardised multivariable Poisson regression model was employed with weekly all-cause deaths the dependent variable for the period 2008–2015. Adjusting for extreme temperature, a total of 26 542 (95% CI 25 301–27 804) deaths in 65+ and 1942 (95% CI 1834–2052) in 15–64-year-olds were associated with influenza from week 40, 2014 to week 20, 2015. This is compatible with the circulation of influenza A(H3N2). It is the largest estimated number of influenza-related deaths in England since prior to 2008/09. The findings highlight the potential health impact of influenza and the important role of the annual influenza vaccination programme that is required to protect the population including the elderly, who are vulnerable to a severe outcome.

Influenza A(H1N1) viruses of the 2009 pandemic (A(H1N1)pdm09) continue to cause outbreaks in the post-pandemic period. During January to May 2015, an upsurge of influenza was recorded that resulted in high fatality in central India. Genetic lineage, mutations in the hemagglutinin (HA) gene and infection by quasi-species are reported to affect disease severity. The objective of this study is to present the molecular and epidemiological trends during the 2015 influenza outbreak in central India. All the referred samples were subjected to qRT–PCR for diagnosis. HA gene sequencing (23 survivors and 24 non-survivors) and cloning were performed and analyzed using Molecular Evolutionary Genomic Analyzer (MEGA 5·05). Of the 3625 tested samples, 1607 (44·3%) were positive for influenza A(H1N1)pdm09, of which 228 (14·2%) individuals succumbed to death. A significant trend was observed in positivity (P = 0·003) and mortality (P < 0·0001) with increasing age. The circulating A(H1N1)pdm09 virus was characterized as belonging to clade-6B. Clinically significant mutations were detected. Patients infected with the quasi-species of the virus had a greater risk of death (P = 0·009). This study proposes a robust molecular and clinical surveillance program for the detection and characterization of the virus, along with prompt treatment protocols to prevent outbreaks.

Computer models can be useful in planning interventions against novel strains of influenza. However such models sometimes make unsubstantiated assumptions about the relative infectivity of asymptomatic and symptomatic cases, or conversely assume there is no impact at all. Using household-level data from known-index studies of virologically confirmed influenza A infection, the relationship between an individual's infectiousness and their symptoms was quantified using a discrete-generation transmission model and Bayesian Markov chain Monte Carlo methods. It was found that the presence of particular respiratory symptoms in an index case does not influence transmission probabilities, with the exception of child-to-child transmission where the donor has phlegm or a phlegmy cough.

The incursion of influenza A(H1N1)pdm09 virus was detected by Norway's active serosurveillance of its pig population in 2009. Since then, surveillance data from 2010 to 2014 revealed that 54% of 5643 herd tests involving 1567 pig herds and 28% of 23 036 blood samples screened positive for antibodies against influenza A virus. Positive herds were confirmed to have influenza A(H1N1)pdm09 virus infection by haemagglutination inhibition test. In 50% of positive herd tests, ⩾60% of the sampled pigs in each herd had antibodies against influenza A(H1N1)pdm09 virus. This within-herd animal seroprevalence did not vary for type of production, herd size or year of test. The overall running mean of national herd seroprevalence, and annual herd incidence risks fluctuated narrowly around the means of 45% and 32%, respectively, with the highest levels recorded in the three densest pig-producing counties. The probability of a herd being seropositive varied in the five production classes, which were sow pools, multiplier herds, conventional sow herds, nucleus herds, and fattening herds in descending order of likelihood. Large herds were more likely to be seropositive. Seropositive herds were highly likely to be seropositive the following year. The study shows that influenza A(H1N1)pdm09 virus is established in the Norwegian pig population with recurrent and new herd infections every year with the national herd seroprevalence in 2014 hovering at around 43% (95% confidence interval 40–46%).

During the early stage of an epidemic, timely and reliable estimation of the severity of infections are important for predicting the impact that the influenza viruses will have in the population. We obtained age-specific deaths and hospitalizations for patients with laboratory-confirmed H1N1pdm09 infections from June 2009 to December 2009 in Hong Kong. We retrospectively obtained the real-time estimates of the hospitalization fatality risk (HFR), using crude estimation or allowing for right-censoring for final status in some patients. Models accounting for right-censoring performed better than models without adjustments. The risk of deaths in hospitalized patients with confirmed H1N1pdm09 increased with age. Reliable estimates of the HFR could be obtained before the peak of the first wave of H1N1pdm09 in young and middle-aged adults but after the peak in the elderly. In the next influenza pandemic, timely estimation of the HFR will contribute to risk assessment and disease control.

Three epidemic waves of human influenza A(H7N9) were documented in several different provinces in China between 2013 and 2015. With limited understanding of the potential for human-to-human transmission, it was difficult to implement control measures efficiently or to inform the public adequately about the application of interventions. In this study, the human-to-human transmission rate for the epidemics that occurred between 2013 and 2015 in Zhejiang Province, China, was analysed. The reproduction number (R), a key indicator of transmission intensity, was estimated by fitting the number of infections from poultry to humans and from humans to humans into a mathematical model. The posterior mean R for human-to-human transmission was estimated to be 0·27, with a 95% credible interval of 0·14–0·44 for the first wave, whereas the posterior mean Rs decreased to 0·15 in the second and third waves. Overall, these estimates indicate that a human H7N9 pandemic is unlikely to occur in Zhejiang. The reductions in the viral transmissibility and the number of poultry-transmitted infections after the first epidemic may be attributable to the various intervention measures taken, including changes in the extent of closures of live poultry markets.

This study aimed to analyse the existence of an association between social class (categorized by type of occupation) and the occurrence of A(H1N1)pmd09 infection and hospitalization for two seasons (2009–2010 and 2010–2011). This multicentre study compared ambulatory A(H1N1)pmd09 confirmed cases with ambulatory controls to measure risk of infection, and with hospitalized A(H1N1)pmd09 confirmed cases to asses hospitalization risk. Study variables were: age, marital status, tobacco and alcohol use, pregnancy, chronic obstructive pulmonary disease, chronic respiratory failure, cardiovascular disease, diabetes, chronic liver disease, body mass index >40, systemic corticosteroid treatment and influenza vaccination status. Occupation was registered literally and coded into manual and non-manual worker occupational social class groups. A conditional logistic regression analysis was performed. There were 720 hospitalized cases, 996 ambulatory cases and 1062 ambulatory controls included in the study. No relationship between occupational social class and A(H1N1)pmd09 infection was found [adjusted odds ratio (aOR) 0·97, 95% confidence interval (CI) 0·74–1·27], but an association (aOR 1·53, 95% CI 1·01–2·31) between occupational class and hospitalization for A(H1N1)pmd09 was observed. Influenza vaccination was a protective factor for A(H1N1)pmd09 infection (aOR 0·41, 95% CI 0·23–0·73) but not for hospitalization. We conclude that manual workers have the highest risk of hospitalization when infected by influenza than other occupations but they do not have a different probability of being infected by influenza.

In March 2013 the first cases of human avian influenza A(H7N9) were reported to the World Health Organization. Since that time, over 650 cases have been reported. Infections are associated with considerable morbidity and mortality, particularly within certain demographic groups. This rapid increase in cases over a brief time period is alarming and has raised concerns about the pandemic potential of the H7N9 virus. Three major factors influence the pandemic potential of an influenza virus: (1) its ability to cause human disease, (2) the immunity of the population to the virus, and (3) the transmission potential of the virus. This paper reviews what is currently known about each of these factors with respect to avian influenza A(H7N9). Currently, sustained human-to-human transmission of H7N9 has not been reported; however, population immunity to the virus is considered very low, and the virus has significant ability to cause human disease. Several statistical and geographical modelling studies have estimated and predicted the spread of the H7N9 virus in humans and avian species, and some have identified potential risk factors associated with disease transmission. Additionally, assessment tools have been developed to evaluate the pandemic potential of H7N9 and other influenza viruses. These tools could also hypothetically be used to monitor changes in the pandemic potential of a particular virus over time.

Understanding patterns of influenza spread and persistence is crucial for pandemic preparedness. The H1N1pdm09 virus caused the first influenza pandemic of the 21st century which resulted in at least 18500 deaths. Based on laboratory-confirmed primary-care case reports we investigated the role of weather conditions and socio-demographic variables in its initial spread and subsequent presence in France. Our findings suggest that low relative humidity and high population density were determinants in shaping the early spread of the virus at the national level. Those conditions also favoured the persistence of viral presence throughout the first 33 weeks of the pandemic. Additionally this persistence was significantly favoured by low insolation. These results confirm the increasingly recognized role of humidity in influenza dynamics and underlie the concomitant effect of insolation. Therefore climatic factors should be taken into account when designing influenza control and prevention measures.

A reassortant swine-origin A(H3N2) virus (A/swine/BinhDuong/03-9/2010) was detected through swine surveillance programmes in southern Vietnam in 2010. This virus contains haemagglutinin and neuraminidase genes from a human A(H3N2) virus circulating around 2004–2006, and the internal genes from triple-reassortant swine influenza A viruses (IAVs). To assess population susceptibility to this virus we measured haemagglutination inhibiting (HI) titres to A/swine/BinhDuong/03-9/2010 and to seasonal A/Perth/16/2009 for 947 sera collected from urban and rural Vietnamese people during 2011–2012. Seroprevalence (HI ⩾ 40) was high and similar for both viruses, with 62·6% [95% confidence interval (CI) 59·4–65·7] against A/Perth/16/2009 and 54·6% (95% CI 51·4–57·8%) against A/swine/BinhDuong/03-9/2010, and no significant differences between urban and rural participants. Children aged <5 years lacked antibodies to the swine origin H3 virus despite high seroprevalence for A/Perth/16/2009. These results reveal vulnerability to infection to this contemporary swine IAV in children aged <5 years; however, cross-reactive immunity in adults would likely limit epidemic emergence potential.

A novel influenza virus emerged in the United States in spring 2009, rapidly becoming a global pandemic. Children were disproportionally affected by the novel influenza A(H1N1) pandemic virus [A(H1N1)pdm]. This retrospective electronic medical record review study aimed to identify clinical predictors of disease severity of influenza A(HIN1)pdm infection in paediatric patients. Disease severity was defined on an increasing three-level scale from non-hospitalized, hospitalized, and admitted to the intensive care unit (ICU). From April 2009 to June 2010, 696 children presented to Texas Children's Hospital's emergency department, 38% were hospitalized, and 17% were admitted to the ICU. Presenting symptoms associated with severe influenza were dyspnoea [odds ratio (OR) 5·82], tachycardia (OR 2·61) and fatigue (OR 1·96). Pre-existing health conditions associated with disease severity included seizure disorder (OR 4·71), obesity (OR 3·28), lung disease (OR 2·84), premature birth (OR 2·53), haematological disease (OR 2·22), and developmental delay (OR 2·20). According to model fitness tests, presenting symptoms were more likely to predict severe influenza than underlying medical conditions. However, both are important risk factors. Recognition of clinical characteristics associated with severe disease can be used for triaging case management of children during future influenza outbreaks.

Avian influenza virus (AIV) is an important zoonotic pathogen, resulting in global human morbidity and mortality and substantial economic losses to the poultry industry. Poultry and wild birds have transmitted AIV to humans, most frequently subtypes H5 and H7, but also different strains and subtypes of H6, H9, and H10. Determining which birds are AIV reservoirs can help identify human populations that have a high risk of infection with these viruses due to occupational or recreational exposure to the reservoir species. To assess the prevalence of AIV in tropical birds, from 2010 to 2014, we sampled 40 099 birds at 32 sites in Central Africa (Cameroon, Central African Republic, Congo-Brazzaville, Gabon) and West Africa (Benin, Côte d'Ivoire, Togo). In Central Africa, detection rates by real-time RT–PCR were 16·6% in songbirds (eight passerine families, n = 1257), 16·4% in kingfishers (family Alcedinidae, n = 73), 8·2% in ducks (family Anatidae, n = 564), and 3·65% in chickens (family Phasianidae, n = 1042). Public health authorities should educate human cohorts that have high exposure to these bird populations about AIV and assess their adherence to biosecurity practices, including Cameroonian farmers who raise small backyard flocks.

A survey of national animal influenza surveillance programmes was conducted to assess the current capacity to detect influenza viruses with zoonotic potential in animals (i.e. those influenza viruses that can be naturally transmitted between animals and humans) at regional and global levels. Information on 587 animal influenza surveillance system components was collected for 99 countries from Chief Veterinary Officers (CVOs) (n = 94) and published literature. Less than 1% (n = 4) of these components were specifically aimed at detecting influenza viruses with pandemic potential in animals (i.e. those influenza viruses that are capable of causing epidemic spread in human populations over large geographical regions or worldwide), which would have zoonotic potential as a prerequisite. Those countries that sought to detect influenza viruses with pandemic potential searched for such viruses exclusively in domestic pigs. This work shows the global need for increasing surveillance that targets potentially zoonotic influenza viruses in relevant animal species.

Effective use of data linkage is becoming an increasingly important focus in the new healthcare system in England. We linked data from the results of a multiplex PCR assay for respiratory viruses for a population of 230 inpatients at a UK teaching hospital with their patient administrative system records in order to compare the mortality and length of stay of patients who tested positive for influenza A(H1N1)pdm09 with those positive for another influenza A virus. The results indicated a reduced risk of death among influenza A(H1N1)pdm09 patients compared to other influenza A strains, with an adjusted risk ratio of 0·25 (95% confidence interval 0·08–0·75, P = 0·01), while no significant differences were found between the lengths of stay in the hospital for these two groups. Further development of such methods to link hospital data in a routine fashion could provide a rapid means of gaining epidemiological insights into emerging infectious diseases.

The age distribution of influenza A(H5N1) cases reported during 2006–2013 varied substantially between countries. As well as underlying demographic profiles, it is possible that cross-immunity contributed to the age distribution of reported cases: seasonal influenza A(H1N1) and avian influenza A(H5N1) share the same neuraminidase subtype, N1. Using a mechanistic model, we measured the extent to which population age distribution and heterosubtypic cross-immunity could explain the observed age patterns in Cambodia, China, Egypt, Indonesia and Vietnam. Our results support experimental evidence that prior infection with H1N1 confers partial cross-immunity to H5N1, and suggest that more than 50% of spillover events did not lead to reported cases of infection as a result. We also identified age groups that have additional risk factors for influenza A(H5N1) not captured by demography or infection history.

Data were extracted from the case records of UK patients admitted with laboratory-confirmed influenza A(H1N1)pdm09. White and non-White patients were characterized by age, sex, socioeconomic status, pandemic wave and indicators of pre-morbid health status. Logistic regression examined differences by ethnicity in patient characteristics, care pathway and clinical outcomes; multivariable models controlled for potential confounders. Whites (n = 630) and non-Whites (n = 510) differed by age, socioeconomic status, pandemic wave of admission, pregnancy, recorded obesity, previous and current smoking, and presence of chronic obstructive pulmonary disease. After adjustment for a priori confounders non-Whites were less likely to have received pre-admission antibiotics [adjusted odds ratio (aOR) 0·43, 95% confidence interval (CI) 0·28–0·68, P < 0·001) but more likely to receive antiviral drugs as in-patients (aOR 1·53, 95% CI 1·08–2·18, P = 0·018). However, there were no significant differences by ethnicity in delayed admission, severity at presentation for admission, or likelihood of severe outcome.

After an outbreak of pandemic influenza A/H1N1 (pH1N1) virus, we had previously reported the emergence of a recombinant canine influenza virus (CIV) between the pH1N1 virus and the classic H3N2 CIV. Our ongoing routine surveillance isolated another reassortant H3N2 CIV carrying the matrix gene of the pH1N1 virus from 2012. The infection dynamics of this H3N2 CIV variant (CIV/H3N2mv) were investigated in dogs and ferrets via experimental infection and transmission. The CIV/H3N2mv-infected dogs and ferrets produced typical symptoms of respiratory disease, virus shedding, seroconversion, and direct-contact transmissions. Although indirect exposure was not presented for ferrets, CIV/H3N2mv presented higher viral replication in MDCK cells and more efficient transmission was observed in ferrets compared to classic CIV H3N2. This study demonstrates the effect of reassortment of the M gene of pH1N1 in CIV H3N2.

In 2009 two notable outbreaks, Q fever and the novel influenza A(H1N1)pdm09, occurred in The Netherlands. Using a composite health measure, disability-adjusted life years (DALYs), the outbreaks were quantified and compared. DALYs were calculated using standardized methodology incorporating age- and sex-stratified data in a disease progression model; years lost due to disability and years of life lost were computed by outcome. Nationally, influenza A(H1N1)pdm09 caused more DALYs (24 484) than Q fever (5797). However, Q fever was 8·28 times more severe [497 DALYs/1000 symptomatic cases (DP1SC)] than A(H1N1)pdm09 (60 DP1SC). The A(H1N1)pdm09 burden is largely due to mortality while the Q fever burden is due primarily to long-term sequelae. Intervention prioritization for influenza should support patients in a critical condition while for Q fever it should target immediate containment and support for patients with long-term sequelae. Burden estimates provide guidance for focusing intervention options during outbreaks of infectious diseases.