2009 Pandemic influenza A H1N1 in Alaska: temporal and geographic characteristics of spread and increased risk of hospitalization among Alaska Native and Asian/Pacific Islander people

Influenza-associated hospitalisation and mortality rates among global Indigenous populations; a systematic review and meta-analysis

BACKGROUND

More than 50 million influenza infections and over 100,000 deaths from influenza occur annually. While Indigenous populations experience an inequitable influenza burden, the magnitude of this inequity has not previously been estimated on a global scale. This study compared rates of influenza-associated hospitalisation and mortality between Indigenous and non-Indigenous populations globally.

METHODS

A systematic review and meta-analysis was conducted including literature published prior to 13 July 2021. Eligible articles either reported a rate ratio (RR) comparing laboratory-confirmed influenza-associated hospitalisation and/or mortality between an Indigenous population and a corresponding benchmark population, or reported sufficient information for this to be calculated using publicly available data. Findings were reported by country/region and pooled by country and period (pandemic/seasonal) when multiple studies were available using a random-effects model. The I2 statistic assessed variability between studies.

RESULTS

Thirty-six studies (moderate/high quality) were included; all from high or high-middle income countries. The pooled influenza-associated hospitalisation RR (HRR) for indigenous compared to benchmark populations was 5·7 (95% CI: 2·7-12·0) for Canada, 5·2 (2.9-9.3) for New Zealand, and 5.2 (4.2-6.4) for Australia. Of the Australian studies, the pooled HRR for seasonal influenza was 3.1 (2·7-3·5) and for pandemic influenza was 6·2 (5·1-7·5). Heterogeneity was slightly higher among studies of pandemic influenza than seasonal influenza. The pooled mortality RR was 4.1 (3·0-5.7) in Australia and 3·3 (2.7-4.1) in the United States.

CONCLUSIONS

Ethnic inequities in severe influenza persist and must be addressed by reducing disparities in the underlying determinants of health. Influenza surveillance systems worldwide should include Indigenous status to determine the extent of the disease burden among Indigenous populations. Ethnic inequities in pandemic influenza illustrate the need to prioritise Indigenous populations in pandemic response plans.

The role of chronic disease in the disparity of influenza incidence and severity between indigenous and non-indigenous Australian peoples during the 2009 influenza pandemic

Background

The 2009 H1N1 influenza pandemic (influenza A(H1N1)pdm09) disproportionately impacted Indigenous peoples. Indigenous Australians are also affected by a health gap in chronic disease prevalence. We hypothesised that the disparity in influenza incidence and severity was accounted for by higher chronic disease prevalence.

Methods

We analysed influenza data from Western Australia, South Australia, the Northern Territory, and Queensland. We calculated population prevalence of chronic diseases in Indigenous and non-Indigenous Australian populations using nationally-collected health survey data. We compared influenza case notifications, hospitalisations, intensive care admissions, and deaths reported amongst the total population of Indigenous and non-Indigenous Australians ≥ 15 years. We accessed age-specific influenza data reported to the Australian Department of Health during the 2009 ‘swine flu’ pandemic, stratified by Indigenous status and the presence of one of five chronic conditions: chronic lower respiratory conditions, diabetes mellitus, obesity, renal disease, and cardiac disease. We calculated age-standardised Indigenous: non-Indigenous rate ratios and confidence intervals.

Findings

Chronic diseases were more prevalent in Indigenous Australians. Rates of influenza diagnoses were higher in Indigenous Australians and more frequent across all indices of severity. In those with chronic conditions, Indigenous: non-Indigenous influenza notification rate ratios were no lower than in the total population; in many instances they were higher. Rate ratios remained above 1·0 at all levels of severity. However, once infected (reflected in notifications), there was no evidence of a further increase in risk of severe outcomes (hospitalisations, ICU admissions, deaths) amongst Indigenous Australians compared to non-Indigenous Australians with a chronic disease.

Interpretation

Higher rates of influenza infection was observed amongst those Indigenous compared to non-Indigenous Australians, and this difference was preserved amongst those with a chronic condition. However, there was no further increase in prevalence of more severe influenza outcomes amongst Indigenous Australians with a chronic condition. This suggests that the prevalence of chronic disease, rather than Indigenous status, affected influenza severity. Other factors may be important, including presence of multiple morbidities, as well as social and cultural determinants of health.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-12841-6.

COVID-19 Cases, Hospitalizations, and Deaths Among American Indian or Alaska Native Persons - Alaska, 2020-2021

American Indian or Alaska Native (AI/AN) persons across the United States face substantial health disparities, including a disproportionately higher incidence of COVID-19 (1,2). AI/AN persons living in Alaska also face serious health and health care challenges, including access to care because 90% of the state's land area is inaccessible by road (3), and approximately one half of the state's AI/AN population (AI/AN race alone or in combination with another race) live in remote rural areas (4). To examine the extent of COVID-19-associated disparities among AI/AN persons living in Alaska, a retrospective analysis of COVID-19 cases reported to the Alaska Department of Health and Social Services (AKDHSS) during March 12, 2020-December 31, 2021, was conducted. The age-adjusted COVID-19 incidence among AI/AN persons was 26,583 per 100,000 standard population, approximately twice the rate among White persons living in Alaska (11,935). The age-adjusted COVID-19-associated hospitalization rate among AI/AN persons was 742 per 100,000, nearly three times the rate among White persons (273) (rate ratio [RR] = 2.72). The age-adjusted COVID-19-related mortality rate among AI/AN persons was 297 per 100,000, approximately three times that among White persons (104; RR = 2.86). Culturally competent public health efforts that are designed in collaboration with AI/AN persons and communities, including support for vaccination and other proven COVID-19 prevention strategies, are critical to reducing COVID-19-associated disparities among AI/AN persons in Alaska.

History Repeating-How Pandemics Collide with Health Disparities in the United States

Across the United States, public health responses to the COVID-19 pandemic have fallen short. COVID-19 has exacerbated longstanding public health shortfalls in disadvantaged communities. Was this predestined? Understanding where we are today requires reflection on our longer journey. Disparities cataloged during COVID-19 reflect the same unequal host exposure and susceptibility risks that shaped previous pandemics. In this review, we provide historical context to better understand current events and to showcase forgotten lessons which may motivate future action to protect our most vulnerable citizens.

SARS-CoV-2 Vaccination Hesitancy and Behaviors in a National Sample of People Living with HIV

As COVID-19 vaccinations became available in early 2021, we collected data from a US national sample of 496 people living with HIV (PLWH) to assess COVID-19 vaccination uptake and attitudes. The study was cross-sectional, and data were collected using an online survey between March and May 2021. At the time, 64% of the participants received at least one dose of a COVID-19 vaccine. Vaccine uptake was associated with older age and more years living with HIV, higher educational attainment, less vaccine hesitancy, and higher perceived COVID-19 vulnerability. Rates of vaccination uptake were highest among sexual and gender minority (SGM) cisgender men and transgender participants as well as those more likely to report undetectable viral load. Among the 166 unvaccinated, intention to receive the vaccine was related to older age and years living with HIV as well as lower vaccine hesitancy. Among the unvaccinated, SGM individuals demonstrated higher intent than non-SGM individuals. Findings indicate relatively high levels of vaccination in PLWH, although uptake and intent are not monolithic in the population. Patterns of vaccination are consistent with the health behavior literature in so much as those with higher levels of perceived heath vulnerability due to age as well as higher levels of proactivity about their HIV health are more likely to be vaccinated or intend to be vaccinated. Ongoing vigilance is required to vaccinate the US population, particularly those with underlying conditions such as HIV, as is the need to tailor health messaging to the highly diverse population of PLWH, with particular emphasis on the intersection of HIV and SGM status.

Black-White Risk Differentials in COVID-19 (SARS-COV2) Transmission, Mortality and Case Fatality in the United States: Translational Epidemiologic Perspective and Challenges

Background: Social and health inequities predispose vulnerable populations to adverse morbidity and mortality outcomes of epidemics and pandemics. While racial disparities in cumulative incidence (CmI) and mortality from the influenza pandemics of 1918 and 2009 implicated Blacks with survival disadvantage relative to Whites in the United States, COVID-19 currently indicates comparable disparities. We aimed to: (a) assess COVID-19 CmI by race, (b) determine the Black–White case fatality (CF) and risk differentials, and (c) apply explanatory model for mortality risk differentials. Methods: COVID-19 data on confirmed cases and deaths by selective states health departments were assessed using a cross-sectional ecologic design. Chi-square was used for CF independence, while binomial regression model for the Black–White risk differentials. Results: The COVID-19 mortality CmI indicated Blacks/AA with 34% of the total mortality in the United States, albeit their 13% population size. The COVID-19 CF was higher among Blacks/AA relative to Whites; Maryland, (2.7% vs. 2.5%), Wisconsin (7.4% vs. 4.8%), Illinois (4.8% vs. 4.2%), Chicago (5.9% vs. 3.2%), Detroit (Michigan), 7.2% and St. John the Baptist Parish (Louisiana), 7.9%. Blacks/AA compared to Whites in Michigan were 15% more likely to die, CmI risk ratio (CmIRR) = 1.15, 95% CI, 1.01–1.32. Blacks/AA relative to Whites in Illinois were 13% more likely to die, CmIRR = 1.13, 95% CI, 0.93–1.39, while Blacks/AA compared to Whites in Wisconsin were 51% more likely to die, CmIRR = 1.51, 95% CI, 1.10–2.10. In Chicago, Blacks/AA were more than twice as likely to die, CmIRR = 2.24, 95% CI, 1.36–3.88. Conclusion: Substantial racial/ethnic disparities are observed in COVID-19 CF and mortality with Blacks/AA disproportionately affected across the United States.

Black-White Risk Differentials in COVID-19 (SARS-COV2) Transmission, Mortality and Case Fatality in the United States: Translational Epidemiologic Perspective and Challenges

BACKGROUND

Social and health inequities predispose vulnerable populations to adverse morbidity and mortality outcomes of epidemics and pandemics. While racial disparities in cumulative incidence (CmI) and mortality from the influenza pandemics of 1918 and 2009 implicated Blacks with survival disadvantage relative to Whites in the United States, COVID-19 currently indicates comparable disparities. We aimed to: (a) assess COVID-19 CmI by race, (b) determine the Black-White case fatality (CF) and risk differentials, and (c) apply explanatory model for mortality risk differentials.

METHODS

COVID-19 data on confirmed cases and deaths by selective states health departments were assessed using a cross-sectional ecologic design. Chi-square was used for CF independence, while binomial regression model for the Black-White risk differentials.

RESULTS

The COVID-19 mortality CmI indicated Blacks/AA with 34% of the total mortality in the United States, albeit their 13% population size. The COVID-19 CF was higher among Blacks/AA relative to Whites; Maryland, (2.7% vs. 2.5%), Wisconsin (7.4% vs. 4.8%), Illinois (4.8% vs. 4.2%), Chicago (5.9% vs. 3.2%), Detroit (Michigan), 7.2% and St. John the Baptist Parish (Louisiana), 7.9%. Blacks/AA compared to Whites in Michigan were 15% more likely to die, CmI risk ratio (CmIRR) = 1.15, 95% CI, 1.01-1.32. Blacks/AA relative to Whites in Illinois were 13% more likely to die, CmIRR = 1.13, 95% CI, 0.93-1.39, while Blacks/AA compared to Whites in Wisconsin were 51% more likely to die, CmIRR = 1.51, 95% CI, 1.10-2.10. In Chicago, Blacks/AA were more than twice as likely to die, CmIRR = 2.24, 95% CI, 1.36-3.88.

CONCLUSION

Substantial racial/ethnic disparities are observed in COVID-19 CF and mortality with Blacks/AA disproportionately affected across the United States.

Health Challenges of the Pacific Region: Insights From History, Geography, Social Determinants, Genetics, and the Microbiome

The Pacific region, also referred to as Oceania, is a geographically widespread region populated by people of diverse cultures and ethnicities. Indigenous people in the region (Melanesians, Polynesians, Micronesians, Papuans, and Indigenous Australians) are over-represented on national, regional, and global scales for the burden of infectious and non-communicable diseases. Although social and environmental factors such as poverty, education, and access to health-care are assumed to be major drivers of this disease burden, there is also developing evidence that genetic and microbiotic factors should also be considered. To date, studies investigating genetic and/or microbiotic links with vulnerabilities to infectious and non-communicable diseases have mostly focused on populations in Europe, Asia, and USA, with uncertain associations for other populations such as indigenous communities in Oceania. Recent developments in personalized medicine have shown that identifying ethnicity-linked genetic vulnerabilities can be important for medical management. Although our understanding of the impacts of the gut microbiome on health is still in the early stages, it is likely that equivalent vulnerabilities will also be identified through the interaction between gut microbiome composition and function with pathogens and the host immune system. As rapid economic, dietary, and cultural changes occur throughout Oceania it becomes increasingly important that further research is conducted within indigenous populations to address the double burden of high rates of infectious diseases and rapidly rising non-communicable diseases so that comprehensive development goals can be planned. In this article, we review the current knowledge on the impact of nutrition, genetics, and the gut microbiome on infectious diseases in indigenous people of the Pacific region.

Investigation of an outbreak of acute respiratory disease in an indigenous village in Brazil: Contribution of Influenza A(H1N1)pdm09 and human respiratory syncytial viruses

Analyses of the 2009 H1N1 influenza pandemic and post-pandemic years showed high attack rates and severity among indigenous populations. This study presents the characteristics of the first documented influenza outbreak in indigenous peoples in Brazil, that occurred from 30th March to 14th April 2016 in a Guarani village in Southeast Region. Acute respiratory infections were prospectively investigated. The majority of the 73 cases were influenza-like illness (ILI) (63.0%) or severe acute respiratory infection (SARI) (20.5%). The ILI+SARI attack rate (35.9%) decreased with increasing age. There was a high influenza vaccination rate (86.3%), but no statistically significant difference in vaccination rates between severe and non-severe cases was seen (p = 0.334). Molecular analyses of 19.2% of the cases showed 100% positivity for influenza A(H1N1)pdm09 and/or hRSV. Influenza A(H1N1)pdm09 was included in the 6B.1 genetic group, a distinct cluster with 13 amino acid substitutions of A/California/07/2009-like. The hRSV were clustered in the BA-like genetic group. The early arrival of the influenza season overlapping usual hRSV season, the circulation of a drifted influenza virus not covered by vaccine and the high prevalence of risk factors for infection and severity in the village jointly can explain the high attack rate of ARI, even with a high rate of influenza vaccination. The results reinforce the importance of surveillance of respiratory viruses, timely vaccination and controlling risk factors for infection and severity of in the indigenous populations in order to preventing disease and related deaths, particularly in children.

Avian influenza virus ecology and evolution through a climatic lens

Avian influenza virus (AIV) is a major health threat to both avian and human populations. The ecology of the virus is driven by numerous factors, including climate and avian migration patterns, yet relatively little is known about these drivers. Long-distance transport of the virus is tied to inter- and intra-continental bird migration, while enhanced viral reassortment is linked to breeding habitats in Beringia shared by migrant species from North America and Asia. Furthermore, water temperature, pH, salinity, and co-existing biota all impact the viability and persistence of the virus in the environment. Changes in climate can potentially alter the ecology of AIV through multiple pathways. Warming temperatures can change the timing and patterns of bird migration, creating novel assemblages of species and new opportunities for viral transport and reassortment. Water temperature and chemistry may also be altered, resulting in changes in virus survival. In this review, we explain how these shifts have the potential to increase viral persistence, pathogenicity, and transmissibility and amplify the threat of pandemic disease in animal and human hosts. Better understanding of climatic influences on viral ecology is essential to developing strategies to limit adverse health effects in humans and animals.

Potentially preventable hospitalizations for acute and chronic conditions in Alaska, 2010-2012

OBJECTIVE

The U.S. Agency for Healthcare Research and Quality's Prevention Quality Indicators comprise acute and chronic conditions for which hospitalization can be potentially prevented by high-quality ambulatory care. The Healthy Alaska 2020 initiative (HA2020) targeted reducing potentially preventable hospitalizations (PPH) for acute and chronic conditions among its health indicators. We estimated the PPH rate for adults aged ≥ 18 years in Alaska during 2010-2012.

METHODS

We conducted a cross-sectional analysis of state-wide hospital discharge data obtained from the Healthcare Cost and Utilization Project and the Indian Health Service. We calculated average annual PPH rates/1000 persons for acute/chronic conditions. Age-adjusted rate ratios (aRRs) were used for evaluating PPH rate disparities between Alaska Native (AN) and non-AN adults.

RESULTS

Among 127,371 total hospitalizations, 4911 and 6721 were for acute and chronic PPH conditions, respectively. The overall crude PPH rate was 7.3 (3.1 for acute and 4.2 for chronic conditions). AN adults had a higher rate than non-AN adults for acute (aRR: 4.7; p < 0.001) and chronic (aRR: 2.6; p < 0.001) PPH conditions. Adults aged ≥ 85 years had the highest PPH rate for acute (43.5) and chronic (31.6) conditions. Acute conditions with the highest PPH rate were bacterial pneumonia (1.8) and urinary tract infections (0.8). Chronic conditions with the highest PPH rate were chronic obstructive pulmonary disease (COPD; 1.6) and congestive heart failure (CHF; 1.3).

CONCLUSION

Efforts to reduce PPHs caused by COPD, CHF, and bacterial pneumonia, especially among AN people and older adults, should yield the greatest benefit in achieving the HA2020 goal.

A case-control study of risk factors for death from 2009 pandemic influenza A(H1N1): is American Indian racial status an independent risk factor?

Historically, American Indian/Alaska Native (AI/AN) populations have suffered excess morbidity and mortality from influenza. We investigated the risk factors for death from 2009 pandemic influenza A(H1N1) in persons residing in five states with substantial AI/AN populations. We conducted a case-control investigation using pandemic influenza fatalities from 2009 in Alaska, Arizona, New Mexico, Oklahoma and Wyoming. Controls were outpatients with influenza. We reviewed medical records and interviewed case proxies and controls. We used multiple imputation to predict missing data and multivariable conditional logistic regression to determine risk factors. We included 145 fatal cases and 236 controls; 22% of cases were AI/AN. Risk factors (P 45 years vs. <18 years], pre-existing medical conditions (mOR 7·1), smoking (mOR 3·0), delayed receipt of antivirals (mOR 6·5), and barriers to healthcare access (mOR 5·3). AI/AN race was not significantly associated with death. The increased influenza mortality in AI/AN individuals was due to factors other than racial status. Prevention of influenza deaths should focus on modifiable factors (smoking, early antiviral use, access to care) and identifying high-risk persons for immunization and prompt medical attention.

Health inequalities and infectious disease epidemics: a challenge for global health security

In today's global society, infectious disease outbreaks can spread quickly across the world, fueled by the rapidity with which we travel across borders and continents. Historical accounts of influenza pandemics and contemporary reports on infectious diseases clearly demonstrate that poverty, inequality, and social determinants of health create conditions for the transmission of infectious diseases, and existing health disparities or inequalities can further contribute to unequal burdens of morbidity and mortality. Yet, to date, studies of influenza pandemic plans across multiple countries find little to no recognition of health inequalities or attempts to engage disadvantaged populations to explicitly address the differential impact of a pandemic on them. To meet the goals and objectives of the Global Health Security Agenda, we argue that international partners, from WHO to individual countries, must grapple with the social determinants of health and existing health inequalities and extend their vision to include these factors so that disease that may start among socially disadvantaged subpopulations does not go unnoticed and spread across borders. These efforts will require rethinking surveillance systems to include sociodemographic data; training local teams of researchers and community health workers who are able to not only analyze data to recognize risk factors for disease, but also use simulation methods to assess the impact of alternative policies on reducing disease; integrating social science disciplines to understand local context; and proactively anticipating shortfalls in availability of adequate healthcare resources, including vaccines. Without explicit attention to existing health inequalities and underlying social determinants of health, the Global Health Security Agenda is unlikely to succeed in its goals and objectives.

Pneumonia and influenza mortality among American Indian and Alaska Native people, 1990-2009

OBJECTIVES

We compared pneumonia and influenza death rates among American Indian/Alaska Native (AI/AN) people with rates among Whites and examined geographic differences in pneumonia and influenza death rates for AI/AN persons.

METHODS

We adjusted National Vital Statistics Surveillance mortality data for racial misclassification of AI/AN people through linkages with Indian Health Service (IHS) registration records. Pneumonia and influenza deaths were defined as those who died from 1990 through 1998 and 1999 through 2009 according to codes for pneumonia and influenza from the International Classification of Diseases, 9th and 10th Revision, respectively. We limited the analysis to IHS Contract Health Service Delivery Area counties, and compared pneumonia and influenza death rates between AI/ANs and Whites by calculating rate ratios for the 2 periods.

RESULTS

Compared with Whites, the pneumonia and influenza death rate for AI/AN persons in both periods was significantly higher. AI/AN populations in the Alaska, Northern Plains, and Southwest regions had rates more than 2 times higher than those of Whites. The pneumonia and influenza death rate for AI/AN populations decreased from 39.6 in 1999 to 2003 to 33.9 in 2004 to 2009.

CONCLUSIONS

Although progress has been made in reducing pneumonia and influenza mortality, disparities between AI/AN persons and Whites persist. Strategies to improve vaccination coverage and address risk factors that contribute to pneumonia and influenza mortality are needed.

Impact of H1N1 on socially disadvantaged populations: summary of a systematic review

BACKGROUND

Previous reviews found that the H1N1 pandemic was associated with a large proportion of hospitalizations, severe illness, workplace absenteeism, and high costs. However, the burden among socially disadvantaged groups of the population is unclear. This is a summary of a previously published systematic review commissioned by the World Health Organization on the burden of H1N1 pandemic (influenza A/Mexico/2009 (H1N1)) among socially disadvantaged populations.

METHODS

MEDLINE and EMBASE were searched to identify studies reporting hospitalization, severe illness, and mortality attributable to the 2009 H1N1 pandemic among socially disadvantaged populations, including ethnic minorities and low-income or lower-middle-income economy countries (LIC/LMIC). SAS and Review Manager were used to conduct random effects meta-analysis.

RESULTS

Forty-eight cohort studies and 14 companion reports including 44 777 patients were included after screening 787 citations and 164 full-text articles. Twelve of the included studies provided data on LIC/LMIC, including one study from Guatemala, two from Morocco, one from Pakistan, and eight from India, plus four companion reports. The rest provided data on ethnic minorities living in high-income economy countries (HIC). Significantly more hospitalizations were observed among ethnic minorities versus nonethnic minorities in two North American studies [1313 patients, odds ratio (OR) 2·26 (95% confidence interval: 1·53-3·32)]. Among hospitalized patients in HIC, statistically significant differences in intensive care unit admissions (n = 8 studies, 15 352 patients, OR 0·84 [0·69-1·02]) and deaths (n = 6 studies, 14 757 patients, OR 0·85 [95% CI: 0·73-1·01]) were not observed.

CONCLUSION

We found significantly more hospitalizations among ethnic minorities versus nonethnic minorities in North America, yet no differences in intensive care unit admissions or deaths among H1N1-infected hospitalized patients were observed in North America and Australia. Our results suggest a similar burden of H1N1 between ethnic minorities and nonethnic minorities living in HIC.

Severe acute respiratory infections caused by 2009 pandemic influenza A (H1N1) among American Indians--southwestern United States, May 1-July 21, 2009

BACKGROUND

During April-July 2009, U.S. hospitalization rates for 2009 pandemic influenza A (H1N1) virus (H1N1pdm09) infection were estimated at 4·5/100 000 persons. We describe rates and risk factors for H1N1pdm09 infection among American Indians (AIs) in four isolated southwestern U.S. communities served by the Indian Health Service (IHS).

METHODS

We reviewed clinical and demographic information from medical records of AIs hospitalized during May 1-July 21, 2009 with severe acute respiratory infection (SARI). Hospitalization rates were determined using denominator data provided by IHS. H1N1pdm09 infection was confirmed with polymerase chain reaction, rapid tests, or convalescent serology. Risk factors for more severe (SARI) versus milder [influenza-like illness (ILI)] illness were determined by comparing confirmed SARI patients with outpatients with ILI.

RESULTS

Among 168 SARI-hospitalized patients, 52% had confirmed H1N1pdm09 infection and 93% had >1 high-risk condition for influenza complications. The H1N1pdm09 SARI hospitalization rate was 131/100 000 persons [95% confidence interval (CI), 102-160] and was highest among ages 0-4 years (353/100 000; 95% CI, 215-492). Among children, asthma (adjusted odds ratio [aOR] 3·2; 95% CI, 1·2-8·4) and age<2 years (aOR 3·8; 95% CI, 1·4-10·0) were associated with H1N1pdm09 SARI-associated hospitalization, compared with outpatient ILI. Among adults, diabetes (aOR 3·1; 95% CI, 1·5-6·4) was associated with hospitalization after controlling for obesity.

CONCLUSIONS

H1N1pdm09 hospitalization rates among this isolated AI population were higher than reported for other U.S. populations. Almost all case patients had high-risk health conditions. Prevention strategies for future pandemics should prioritize AIs, particularly in isolated rural areas.

Pandemic influenza A (H1N1) in non-vaccinated, pregnant women in Spain (2009-2010)

The aim of this study was to investigate the main characteristics of non-vaccinated pregnant women who were hospitalised for influenza A (H1N1) pdm09 pandemic versus pregnant women hospitalised for non-influenza-related reasons in Spain, and to characterise the clinical presentation of the disease in this population to facilitate early diagnosis and future action programmes. Understanding influenza infection during pregnancy is important as pregnant women are a high-risk population for increased morbidity from influenza infection. We investigated the socio-demographic and clinical features of 51 non-vaccinated, pregnant women infected with the pandemic influenza A (H1N1) virus in Spain (cases) and compared them to 114 controls (non-vaccinated and non-infected pregnant women) aged 15-44 years. Substantial and significant odd ratios (ORs) for pandemic influenza A (H1N1) were found for the pregnant women who were obese compared with controls (body mass index > 30) (OR 3.03; 95% confidence intervals 1.13-8.11). The more prevalent symptoms observed in pandemic influenza-infected pregnant women were high temperature, cough (82.4%), malaise (80.5%), myalgia (56.1%), and headaches (54.9%). Our results suggest that the initial symptoms and risk factors for infection of pregnant women with the influenza A (H1N1) pdm09 virus are similar to the symptoms and risk factors for seasonal influenza, which make early diagnosis difficult, and reinforces the need to identify and protect high-risk groups.

Increasing trend in the rate of infectious disease hospitalisations among Alaska Native people

OBJECTIVES

To examine the epidemiology of infectious disease (ID) hospitalisations among Alaska Native (AN) people.

METHODS

Hospitalisations with a first-listed ID diagnosis for American Indians and ANs residing in Alaska during 2001-2009 were selected from the Indian Health Service direct and contract health service inpatient data. ID hospitalisations to describe the general US population were selected from the Nationwide Inpatient Sample. Annual and average annual (2007-2009) hospitalization rates were calculated.

RESULTS

During 2007-2009, IDs accounted for 20% of hospitalisations among AN people. The 2007-2009 average annual age-adjusted ID hospitalisation rate (2126/100,000 persons) was higher than that for the general US population (1679/100,000; 95% CI 1639-1720). The ID hospitalisation rate for AN people increased from 2001 to 2009 (17%, p < 0.001). Although the rate during 2001-2009 declined for AN infants (< 1 year of age; p = 0.03), they had the highest 2007-2009 average annual rate (15106/100,000), which was 3 times the rate for general US infants (5215/100,000; 95% CI 4783-5647). The annual rates for the age groups 1-4, 5-19, 40-49, 50-59 and 70-79 years increased (p < 0.05). The highest 2007-2009 age-adjusted average annual ID hospitalisation rates were in the Yukon-Kuskokwim (YK) (3492/100,000) and Kotzebue (3433/100,000) regions; infant rates were 30422/100,000 and 26698/100,000 in these regions, respectively. During 2007-2009, lower respiratory tract infections accounted for 39% of all ID hospitalisations and approximately 50% of ID hospitalisations in YK, Kotzebue and Norton Sound, and 74% of infant ID hospitalisations.

CONCLUSIONS

The ID hospitalisation rate increased for AN people overall. The rate for AN people remained higher than that for the general US population, particularly in infants and in the YK and Kotzebue regions. Prevention measures to reduce ID morbidity among AN people should be increased in high-risk regions and for diseases with high hospitalisation rates.

Comparative spatial dynamics of Japanese encephalitis and acute encephalitis syndrome in Nepal

Japanese Encephalitis (JE) is a vector-borne disease of major importance in Asia. Recent increases in cases have spawned the development of more stringent JE surveillance. Due to the difficulty of making a clinical diagnosis, increased tracking of common symptoms associated with JE-generally classified as the umbrella term, acute encephalitis syndrome (AES) has been developed in many countries. In Nepal, there is some debate as to what AES cases are, and how JE risk factors relate to AES risk. Three parts of this analysis included investigating the temporal pattern of cases, examining the age and vaccination status patterns among AES surveillance data, and then focusing on spatial patterns of risk factors. AES and JE cases from 2007-2011 reported at a district level (n = 75) were examined in relation to landscape risk factors. Landscape pattern indices were used to quantify landscape patterns associated with JE risk. The relative spatial distribution of landscape risk factors were compared using geographically weighted regression. Pattern indices describing the amount of irrigated land edge density and the degree of landscape mixing for irrigated areas were positively associated with JE and AES, while fragmented forest measured by the number of forest patches were negatively associated with AES and JE. For both JE and AES, the local GWR models outperformed global models, indicating spatial heterogeneity in risks. Temporally, the patterns of JE and AES risk were almost identical; suggesting the relative higher caseload of AES compared to JE could provide a valuable early-warning signal for JE surveillance and reduce diagnostic testing costs. Overall, the landscape variables associated with a high degree of landscape mixing and small scale irrigated agriculture were positively linked to JE and AES risk, highlighting the importance of integrating land management policies, disease prevention strategies and promoting healthy sustainable livelihoods in both rural and urban-fringe developing areas.

Influenza surveillance using electronic health records in the American Indian and Alaska Native population

OBJECTIVE

Increasing use of electronic health records (EHRs) provides new opportunities for public health surveillance. During the 2009 influenza A (H1N1) virus pandemic, we developed a new EHR-based influenza-like illness (ILI) surveillance system designed to be resource sparing, rapidly scalable, and flexible. 4 weeks after the first pandemic case, ILI data from Indian Health Service (IHS) facilities were being analyzed.

MATERIALS AND METHODS

The system defines ILI as a patient visit containing either an influenza-specific International Classification of Disease, V.9 (ICD-9) code or one or more of 24 ILI-related ICD-9 codes plus a documented temperature ≥100°F. EHR-based data are uploaded nightly. To validate results, ILI visits identified by the new system were compared to ILI visits found by medical record review, and the new system's results were compared with those of the traditional US ILI Surveillance Network.

RESULTS

The system monitored ILI activity at an average of 60% of the 269 IHS electronic health databases. EHR-based surveillance detected ILI visits with a sensitivity of 96.4% and a specificity of 97.8% based on chart review (N=2375) of visits at two facilities in September 2009. At the peak of the pandemic (week 41, October 17, 2009), the median time from an ILI visit to data transmission was 6 days, with a mode of 1 day.

DISCUSSION

EHR-based ILI surveillance was accurate, timely, occurred at the majority of IHS facilities nationwide, and provided useful information for decision makers. EHRs thus offer the opportunity to transform public health surveillance.

Does outpatient laboratory testing represent influenza burden and distribution in a rural state?

Background

Laboratory testing results are often used to monitor influenza illness in populations, but results may not be representative of illness burden and distribution, especially in populations that are geographically, socioeconomically, and racially/ethnically diverse.

Objectives

Descriptive epidemiology and chi‐square analyses using demographic, geographic, and medical condition prevalence comparisons were employed to assess whether a group of individuals with outpatient laboratory‐confirmed influenza illness during September–November 2009 represented the burden and distribution of influenza illness in New Mexico (NM).

Patients/Methods

The outpatient group was identified via random selection from those with positive influenza tests at NM laboratories. Comparison groups included those with laboratory‐confirmed H1N1‐related influenza hospitalization and death identified via prospective active statewide surveillance, those with self‐reported influenza‐like illness (ILI) identified through random digit dialing, and the NM population.

Results

This analysis included 334 individuals with outpatient laboratory‐confirmed influenza, 888 individuals with laboratory‐confirmed H1N1‐related hospitalization, 39 individuals with laboratory‐confirmed H1N1‐related death, 334 individuals with ILI, and NM population data (N = 2 036 112). The outpatient laboratory‐confirmed group had a different distribution of demographic and geographic factors, as well as prevalence of certain medical conditions as compared to the groups of laboratory‐confirmed H1N1‐related hospitalization and death, the ILI group, and the NM population.

Conclusions

The outpatient laboratory‐confirmed group may reflect provider testing practices and potentially healthcare‐seeking behavior and access to care, rather than influenza burden and distribution in NM during the H1N1 pandemic.

Impact of H1N1 on socially disadvantaged populations: systematic review

BACKGROUND

The burden of H1N1 among socially disadvantaged populations is unclear. We aimed to synthesize hospitalization, severe illness, and mortality data associated with pandemic A/H1N1/2009 among socially disadvantaged populations.

METHODS/PRINCIPAL FINDINGS

Studies were identified through searching MEDLINE, EMBASE, scanning reference lists, and contacting experts. Studies reporting hospitalization, severe illness, and mortality attributable to laboratory-confirmed 2009 H1N1 pandemic among socially disadvantaged populations (e.g., ethnic minorities, low-income or lower-middle-income economy countries [LIC/LMIC]) were included. Two independent reviewers conducted screening, data abstraction, and quality appraisal (Newcastle Ottawa Scale). Random effects meta-analysis was conducted using SAS and Review Manager.

CONCLUSIONS/SIGNIFICANCE

Sixty-two studies including 44,777 patients were included after screening 787 citations and 164 full-text articles. The prevalence of hospitalization for H1N1 ranged from 17-87% in high-income economy countries (HIC) and 11-45% in LIC/LMIC. Of those hospitalized, the prevalence of intensive care unit (ICU) admission and mortality was 6-76% and 1-25% in HIC; and 30% and 8-15%, in LIC/LMIC, respectively. There were significantly more hospitalizations among ethnic minorities versus non-ethnic minorities in two studies conducted in North America (1,313 patients, OR 2.26 [95% CI: 1.53-3.32]). There were no differences in ICU admissions (n = 8 studies, 15,352 patients, OR 0.84 [0.69-1.02]) or deaths (n = 6 studies, 14,757 patients, OR 0.85 [95% CI: 0.73-1.01]) among hospitalized patients in HIC. Sub-group analysis indicated that the meta-analysis results were not likely affected by confounding. Overall, the prevalence of hospitalization, severe illness, and mortality due to H1N1 was high for ethnic minorities in HIC and individuals from LIC/LMIC. However, our results suggest that there were little differences in the proportion of hospitalization, severe illness, and mortality between ethnic minorities and non-ethnic minorities living in HIC.

The spread of influenza A(H1N1)pdm09 virus in Madagascar described by a sentinel surveillance network

Background

The influenza A(H1N1)pdm09 virus has been a challenge for public health surveillance systems in all countries. In Antananarivo, the first imported case was reported on August 12, 2009. This work describes the spread of A(H1N1)pdm09 in Madagascar.

Methods

The diffusion of influenza A(H1N1)pdm09 in Madagascar was explored using notification data from a sentinel network. Clinical data were charted to identify peaks at each sentinel site and virological data was used to confirm viral circulation.

Results

From August 1, 2009 to February 28, 2010, 7,427 patients with influenza-like illness were reported. Most patients were aged 7 to 14 years. Laboratory tests confirmed infection with A(H1N1)pdm09 in 237 (33.2%) of 750 specimens. The incidence of patients differed between regions. By determining the epidemic peaks we traced the diffusion of the epidemic through locations and time in Madagascar. The first peak was detected during the epidemiological week 47-2009 in Antananarivo and the last one occurred in week 07-2010 in Tsiroanomandidy.

Conclusion

Sentinel surveillance data can be used for describing epidemic trends, facilitating the development of interventions at the local level to mitigate disease spread and impact.

Geographic distribution and risk factors of the initial adult hospitalized cases of 2009 pandemic influenza A (H1N1) virus infection in mainland China

Background

As of 31^st March 2010, more than 127,000 confirmed cases of 2009 pandemic influenza A (H1N1), including 800 deaths, were reported in mainland China. The distribution and characteristics of the confirmed cases in the initial phase of this pandemic in this country are largely unknown. The present study aimed to characterize the geographic distribution and patient characteristics of H1N1 infection in the 2009 pandemic as well as to identify potential risk factors associated with adverse patient outcome in China, through retrospective analyses of 885 hospitalized cases with confirmed H1N1 infection.

Methodology/Principal Findings

The proportional hazards model was employed to detect risk factors for adverse outcome; the geo-statistical maps were used to characterize the distribution of all 2668 confirmed H1N1 patients throughout mainland China. The number of new cases increased slowly in May, 2009, but rapidly between June and August of the year. Confirmed cases were reported in 26 provinces; Beijing, Guangdong, Shanghai, Zhejiang and Fujian were the top five regions of the incidence of the virus infection. After being adjusted for gender, age, chronic pulmonary disease and other general symptoms, delay for more than two days before hospital admission (HR: 0.6; 95%CI: 0.5–0.7) and delayed onset of the H1N1-specific respiratory symptoms (HR: 0.3; 95%CI: 0.2–0.4) were associated with adverse patient outcome.

Conclusions/Significance

The 2009 pandemic influenza A affected east and southeast coastal provinces and most populous cities more severely than other regions in mainland China due to higher risk of high level traffic-, high population density-, and high population mobility-associated H1N1 transmission.The clinical symptoms were mild in the initial phase of infection. Delayed hospital admission and delayed appearance of respiratory symptoms were among the major risk factors for poor patient outcome. These findings may have significant implications in the future pandemic preparedness and response.