El Niño effects on influenza mortality risks in the state of California

How do El Niño Southern Oscillation (ENSO) and local meteorological factors affect the incidence of seasonal influenza in New York state

Background

Research is lacking in examining how multiple climate factors affect the incidence of seasonal influenza. We investigated the associations between El Niño Southern Oscillation (ENSO), meteorological factors, and influenza incidence in New York State, United States.

Method

We collected emergency department visit data for influenza from the New York State Department of Health. ENSO index was obtained from the National Oceanic and Atmospheric Administration. Meteorological factors, Google Flu Search Index (GFI), and Influenza-like illness (ILI) data in New York State were also collected. Wavelet analysis was used to quantitatively estimate the coherence and phase difference of ENSO, temperature, precipitation, relative humidity, and absolute humidity with emergency department visits of influenza in New York State. Generalized additive models (GAM) were employed to examine the exposure-response relationships between ENSO, weather, and influenza. GFI and ILI data were used to simulate synchronous influenza visits.

Results

The influenza epidemic in New York State had multiple periodic and was primarily on the 1-year scale. The incidence of influenza closely followed the low ENSO index by an average of two months, and the lag period of ENSO on influenza was shorter during 2015-2018. Low temperature in the previous 2 weeks and low absolute humidity in the prior week were positively associated with influenza incidence in New York State. We found an l-shaped association between ENSO index and influenza, a parabolic relationship between temperature in the previous two weeks and influenza, and a linear negative association between absolute humidity in the previous week and influenza. The simulation models including GFI and ILI had higher accuracy for influenza visit estimation.

Conclusions

Low ENSO index, low temperature, and low absolute humidity may drive the influenza epidemics in New York State. The findings can help us deepen the understanding of the climate-influenza association, and help to develop an influenza forecasting model.

The association between the seasonality of pediatric pandemic influenza virus outbreak and ambient meteorological factors in Shanghai

BACKGROUND AND OBJECTIVES

The number of pediatric patients diagnosed with influenza types A and B is increasing annually, especially in temperate regions such as Shanghai (China). The onset of pandemic influenza viruses might be attributed to various ambient meteorological factors including temperature, relative humidity (Rh), and PM₁ concentrations, etc. The study aims to explore the correlation between the seasonality of pandemic influenza and these factors.

METHODS

We recruited pediatric patients aged from 0 to 18 years who were diagnosed with influenza A or B from July 1st, 2017 to June 30th, 2019 in Shanghai Children's Medical Centre (SCMC). Ambient meteorological data were collected from the Shanghai Meteorological Service (SMS) over the same period. The correlation of influenza outbreak and meteorological factors were analyzed through preliminary Pearson's r correlation test and subsequent time-series Poisson regression analysis using the distributed lag non-linear model (DLNM).

RESULTS

Pearson's r test showed a statistically significant correlation between the weekly number of influenza A outpatients and ambient meteorological factors including weekly mean, maximum, minimum temperature and barometric pressure (P < 0.001), and PM₁ (P < 0.01). While the weekly number of influenza B outpatients was statistically significantly correlated with weekly mean, maximum and minimum temperature (P < 0.001), barometric pressure and PM₁ (P < 0.01), and minimum Rh (P < 0.05). Mean temperature and PM₁ were demonstrated to be the statistically significant variables in the DLNM with influenza A and B outpatients through time-series Poisson regression analysis. A U-shaped curve relationship was noted between the mean temperature and influenza A cases (below 15 °C and above 20 °C), and the risks increased for influenza B with mean temperature below 10 °C. PM₁ posed a risk after a concentration of 23 ppm for both influenza A and B. High PM₁, low and the high temperature had significant effects upon the number of influenza A cases, whereas low temperature and high PM₁ had significant effects upon the number of influenza B cases.

CONCLUSION

This study indicated that mean temperature and PM₁ were the primary factors that were continually associated with the seasonality of pediatric pandemic influenza A and B and the recurrence in the transmission and spread of influenza viruses.

Impact of El Niño Southern Oscillation on infectious disease hospitalization risk in the United States

Although the global climate is changing at an unprecedented rate, links between weather and infectious disease have received little attention in high income countries. The "El Niño Southern Oscillation" (ENSO) occurs irregularly and is associated with changing temperature and precipitation patterns. We studied the impact of ENSO on infectious diseases in four census regions in the United States. We evaluated infectious diseases requiring hospitalization using the US National Hospital Discharge Survey (1970-2010) and five disease groupings that may undergo epidemiological shifts with changing climate: (i) vector-borne diseases, (ii) pneumonia and influenza, (iii) enteric disease, (iv) zoonotic bacterial disease, and (v) fungal disease. ENSO exposure was based on the Multivariate ENSO Index. Distributed lag models, with adjustment for seasonal oscillation and long-term trends, were used to evaluate the impact of ENSO on disease incidence over lags of up to 12 mo. ENSO was associated more with vector-borne disease [relative risk (RR) 2.96, 95% confidence interval (CI) 1.03-8.48] and less with enteric disease (0.73, 95% CI 0.62-0.87) in the Western region; the increase in vector-borne disease was attributable to increased risk of rickettsioses and tick-borne infectious diseases. By contrast, ENSO was associated with more enteric disease in non-Western regions (RR 1.12, 95% CI 1.02-1.15). The periodic nature of ENSO may make it a useful natural experiment for evaluation of the impact of climatic shifts on infectious disease risk. The impact of ENSO suggests that warmer temperatures and extreme variation in precipitation events influence risks of vector-borne and enteric disease in the United States.

The rise and fall of infectious disease in a warmer world

Now-outdated estimates proposed that climate change should have increased the number of people at risk of malaria, yet malaria and several other infectious diseases have declined. Although some diseases have increased as the climate has warmed, evidence for widespread climate-driven disease expansion has not materialized, despite increased research attention. Biological responses to warming depend on the non-linear relationships between physiological performance and temperature, called the thermal response curve. This leads performance to rise and fall with temperature. Under climate change, host species and their associated parasites face extinction if they cannot either thermoregulate or adapt by shifting phenology or geographic range. Climate change might also affect disease transmission through increases or decreases in host susceptibility and infective stage (and vector) production, longevity, and pathology. Many other factors drive disease transmission, especially economics, and some change in time along with temperature, making it hard to distinguish whether temperature drives disease or just correlates with disease drivers. Although it is difficult to predict how climate change will affect infectious disease, an ecological approach can help meet the challenge.

Climate variability and nonstationary dynamics of Mycoplasma pneumoniae pneumonia in Japan

Background

A stationary association between climate factors and epidemics of Mycoplasma pneumoniae (M. pneumoniae) pneumonia has been widely assumed. However, it is unclear whether elements of the local climate that are relevant to M. pneumoniae pneumonia transmission have stationary signatures of climate factors on their dynamics over different time scales.

Methods

We performed a cross-wavelet coherency analysis to assess the patterns of association between monthly M. pneumoniae cases in Fukuoka, Japan, from 2000 to 2012 and indices for the Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO).

Results

Monthly M. pneumoniae cases were strongly associated with the dynamics of both the IOD and ENSO for the 1–2-year periodic mode in 2005–2007 and 2010–2011. This association was non-stationary and appeared to have a major influence on the synchrony of M. pneumoniae epidemics.

Conclusions

Our results call for the consideration of non-stationary, possibly non-linear, patterns of association between M. pneumoniae cases and climatic factors in early warning systems.

Climate variability and outbreaks of infectious diseases in Europe

Several studies provide evidence of a link between vector-borne disease outbreaks and El Niño driven climate anomalies. Less investigated are the effects of the North Atlantic Oscillation (NAO). Here, we test its impact on outbreak occurrences of 13 infectious diseases over Europe during the last fifty years, controlling for potential bias due to increased surveillance and detection. NAO variation statistically influenced the outbreak occurrence of eleven of the infectious diseases. Seven diseases were associated with winter NAO positive phases in northern Europe, and therefore with above-average temperatures and precipitation. Two diseases were associated with the summer or spring NAO negative phases in northern Europe, and therefore with below-average temperatures and precipitation. Two diseases were associated with summer positive or negative NAO phases in southern Mediterranean countries. These findings suggest that there is potential for developing early warning systems, based on climatic variation information, for improved outbreak control and management.

The El Nino-Southern Oscillation (ENSO)-pandemic influenza connection: coincident or causal?

We find that the four most recent human influenza pandemics (1918, 1957, 1968, and 2009), all of which were first identified in boreal spring or summer, were preceded by La Niña conditions in the equatorial Pacific. Changes in the phase of the El Niño-Southern Oscillation have been shown to alter the migration, stopover time, fitness, and interspecies mixing of migratory birds, and consequently, likely affect their mixing with domestic animals. We hypothesize that La Niña conditions bring divergent influenza subtypes together in some parts of the world and favor the reassortment of influenza through simultaneous multiple infection of individual hosts and the generation of novel pandemic strains. We propose approaches to test this hypothesis using influenza population genetics, virus prevalence in various host species, and avian migration patterns.

Climate change and infectious diseases in New Zealand: a brief review and tentative research agenda

AIMS

To review the literature on infectious diseases and meteorological and climate change risk factors in the New Zealand context and to describe a tentative research agenda for future work.

METHODS

We performed literature searches in May 2010 using Medline and Google Scholar. We also searched five health-related government agencies in New Zealand for documentation on climate change and health.

RESULTS

The effect of climate variability and change on vector-borne disease has been considered in more detail than any other infectious disease topic (n=20+ journal articles and reports relating to New Zealand). Generally, concern has arisen around the risk of new mosquito incursions and increased risks of dengue and Ross River fevers in the long term. For enteric diseases, the picture from five New Zealand publications is somewhat mixed, although the data indicate that salmonellosis notifications increase with higher monthly temperatures. One interpretation of the New Zealand data is that communities without reticulated water supplies could be more vulnerable to the effects of climate change-mediated increases in protozoan diseases. This information informed a tentative research agenda to address research gaps. Priorities include the need for further work on a more integrated surveillance framework, vector-borne diseases, enteric diseases, skin infections, and then work on topics for which we found no published New Zealand work (such as influenza and leptospirosis). Finally, we found that health-related government agencies in New Zealand have relatively little 'climate change and health' information on their websites.

CONCLUSIONS

Although some informative work has been done to date, much scope remains for additional research and planning to facilitate prevention, mitigation, and adaptation responses in the New Zealand setting around climate change and infectious disease risks. The tentative research agenda produced could benefit from a wider critique, and government agencies in New Zealand could contribute to informed discussions by better documenting the current state of knowledge on their websites.

Climate change and health in british columbia: projected impacts and a proposed agenda for adaptation research and policy

This is a case study describing how climate change may affect the health of British Columbians and to suggest a way forward to promote health and policy research, and adaptation to these changes. After reviewing the limited evidence of the impacts of climate change on human health we have developed five principles to guide the development of research and policy to better predict future impacts of climate change on health and to enhance adaptation to these change in BC. We suggest that, with some modification, these principles will be useful to policy makers in other jurisdictions.

Climate change and infectious diseases in Europe

Concerted action is needed to address public health issues raised by climate change. In this Review we discuss infections acquired through various routes (arthropod vector, rodent, water, food, and air) in view of a changing climate in Europe. Based on an extensive review of published work and expert workshops, we present an assessment of the infectious disease challenges: incidence, prevalence, and distribution are projected to shift in a changing environment. Due to the high level of uncertainty on the rate of climate change and its impact on infectious diseases, we propose to mount a proactive public health response by building an integrated network for environmental and epidemiological data. This network would have the capacity to connect epidemic intelligence and infectious disease surveillance with meteorological, entomological, water quality, remote sensing, and other data, for multivariate analyses and predictions. Insights from these analyses could then guide adaptation strategies and protect population health from impending threats related to climate change.

A spatiotemporal statistical model of the risk factors of human cases of H5N1 avian influenza in South-east Asian countries and China

OBJECTIVES

This article aims to quantify the risk factors associated with the human cases of H5N1 avian influenza in South-east Asian countries and China; a dangerous region for this disease that has the potential for a pandemic outbreak.

STUDY DESIGN

A statistical model with time and spatial dimensions was built to capture the international spread patterns of this disease.

METHODS

The grid search method was used to fit the model with 2004-2006 data. The grid search approach is a simple procedure that allows the fit of any function to data.

RESULTS

This study found that: (1) when the number of domestic H5N1 human cases increases by one person in a certain time period, the chance that the country will have a human case in the next period increases by 22.10%; (2) when the number of human cases in a neighbouring country increases by one person in a certain time period, the chance that the country will have a human case in the next period increases by 1.62%; (3) when the number of avian cases in a neighbouring country increases by one, the chance that the country will have a human case increases by 0.02%; (4) as the human population increases by one unit, the chance that the country will have a human case increases by 0.10%; (5) when the quantity of imported poultry increases by 1000 metric tons, the chance that the country will have a human case increases by 0.03%; (6) when the outbreak of the disease among domestic birds increases by one, the chance that the country will have a human case increases by 0.19%; and finally (7) when the number of birds destroyed increases by 1000, the chance that the country will have a human case decreases by 0.30%.

CONCLUSIONS

These findings shed new light on the spatiotemporal characteristics of the epidemic, and thus need to be taken into consideration in interdisciplinary and scientific discussion of the disease.

Climate change and infectious diseases in North America: the road ahead

Global climate change is inevitable--the combustion of fossil fuels has resulted in a buildup of greenhouse gases within the atmosphere, causing unprecedented changes to the earth's climate. The Fourth Assessment Report of the Intergovernmental Panel on Climate Change suggests that North America will experience marked changes in weather patterns in coming decades, including warmer temperatures and increased rainfall, summertime droughts and extreme weather events (e.g., tornadoes and hurricanes). Although these events may have direct consequences for health (e.g., injuries and displacement of populations due to thermal stress), they are also likely to cause important changes in the incidence and distribution of infectious diseases, including vector-borne and zoonotic diseases, water-and food-borne diseases and diseases with environmental reservoirs (e.g., endemic fungal diseases). Changes in weather patterns and ecosystems, and health consequences of climate change will probably be most severe in far northern regions (e.g., the Arctic). We provide an overview of the expected nature and direction of such changes, which pose current and future challenges to health care providers and public health agencies.