RT-PCR genotyping assays to identify SARS-CoV-2 variants in England in 2021: a design and retrospective evaluation study

BACKGROUND

Whole-genome sequencing (WGS) is the gold standard diagnostic tool to identify and genetically characterise emerging pathogen mutations (variants), but cost, capacity, and timeliness limit its use when large populations need rapidly assessing. We assessed the potential of genotyping assays to provide accurate and timely variant information at scale by retrospectively examining surveillance for SARS-CoV-2 variants in England between March and September, 2021, when genotyping assays were used widely for variant detection.

METHODS

We chose a panel of four RT-PCR genotyping assays to detect circulating variants of SARS-COV-2 in England and developed a decision algorithm to assign a probable SARS-CoV-2 variant to samples using the assay results. We extracted surveillance data from the UK Health Security Agency databases for 115 934 SARS-CoV-2-positive samples (March 1-Sept 6, 2021) when variant information was available from both genotyping and WGS. By comparing the genotyping and WGS variant result, we calculated accuracy metrics (ie, sensitivity, specificity, and positive predictive value [PPV]) and the time difference between the sample collection date and the availability of variant information. We assessed the number of samples with a variant assigned from genotyping or WGS, or both, over time.

FINDINGS

Genotyping and an initial decision algorithm (April 10-May 11, 2021 data) were accurate for key variant assignment: sensitivities and PPVs were 0·99 (95% CI 0·99-0·99) for the alpha, 1·00 (1·00-1·00) for the beta, and 0·91 (0·80-1·00) for the gamma variants; specificities were 0·97 (0·96-0·98), 1·00 (1·00-1·00), and 1·00 (1·00-1·00), respectively. A subsequent decision algorithm over a longer time period (May 27-Sept 6, 2021 data) remained accurate for key variant assignment: sensitivities were 0·91 (95% CI 0·74-1·00) for the beta, 0·98 (0·98-0·99) for the delta, and 0·93 (0·81-1·00) for the gamma variants; specificities were 1·00 (1·00-1·00), 0·96 (0·96-0·97), and 1·00 (1·00-1·00), respectively; and PPVs were 0·83 (0·62-1·00), 1·00 (1·00-1·00), and 0·78 (0·59-0·97), respectively. Genotyping produced variant information a median of 3 days (IQR 2-4) after the sample collection date, which was faster than with WGS (9 days [8-11]). The flexibility of genotyping enabled a nine-times increase in the quantity of samples tested for variants by this method (from 5000 to 45 000).

INTERPRETATION

RT-PCR genotyping assays are suitable for high-throughput variant surveillance and could complement WGS, enabling larger scale testing for known variants and timelier results, with important implications for effective public health responses and disease control globally, especially in settings with low WGS capacity. However, the choice of panels of RT-PCR assays is highly dependent on database information on circulating variants generated by WGS, which could limit the use of genotyping assays when new variants are emerging and spreading rapidly.

FUNDING

UK Health Security Agency and National Institute for Health Research Health Protection Research Unit in Emergency Preparedness and Response.

Effectiveness of filtering or decontaminating air to reduce or prevent respiratory infections: A systematic review

Installation of technologies to remove or deactivate respiratory pathogens from indoor air is a plausible non-pharmaceutical infectious disease control strategy.

OBJECTIVE

We undertook a systematic review of worldwide observational and experimental studies, published 1970-2022, to synthesise evidence about the effectiveness of suitable indoor air treatment technologies to prevent respiratory or gastrointestinal infections.

METHODS

We searched for data about infection and symptom outcomes for persons who spent minimum 20 h/week in shared indoor spaces subjected to air treatment strategies hypothesised to change risk of respiratory or gastrointestinal infections or symptoms.

RESULTS

Pooled data from 32 included studies suggested no net benefits of air treatment technologies for symptom severity or symptom presence, in absence of confirmed infection. Infection incidence was lower in three cohort studies for persons exposed to high efficiency particulate air filtration (RR 0.4, 95%CI 0.28-0.58, p < 0.001) and in one cohort study that combined ionisers with electrostatic nano filtration (RR 0.08, 95%CI 0.01-0.60, p = 0.01); other types of air treatment technologies and air treatment in other study designs were not strongly linked to fewer infections. The infection outcome data exhibited strong publication bias.

CONCLUSIONS

Although environmental and surface samples are reduced after air treatment by several air treatment strategies, especially germicidal lights and high efficiency particulate air filtration, robust evidence has yet to emerge that these technologies are effective at reducing respiratory or gastrointestinal infections in real world settings. Data from several randomised trials have yet to report and will be welcome to the evidence base.

Comparison of surveillance systems for monitoring COVID-19 in England: a retrospective observational study

BACKGROUND

During the COVID-19 pandemic, cases were tracked using multiple surveillance systems. Some systems were completely novel, and others incorporated multiple data streams to estimate case incidence and prevalence. How well these different surveillance systems worked as epidemic indicators is unclear, which has implications for future disease surveillance and outbreak management. The aim of this study was to compare case counts, prevalence and incidence, timeliness, and comprehensiveness of different COVID-19 surveillance systems in England.

METHODS

For this retrospective observational study of COVID-19 surveillance systems in England, data from 12 surveillance systems were extracted from publicly available sources (Jan 1, 2020-Nov 30, 2021). The main outcomes were correlations between different indicators of COVID-19 incidence or prevalence. These data were integrated as daily time-series and comparisons undertaken using Spearman correlation between candidate alternatives and the most timely (updated daily, clinical case register) and the least biased (from comprehensive household sampling) COVID-19 epidemic indicators, with comparisons focused on the period of Sept 1, 2020-Nov 30, 2021.

FINDINGS

Spearman statistic correlations during the full focus period between the least biased indicator (from household surveys) and other epidemic indicator time-series were 0·94 (95% CI 0·92 to 0·95; clinical cases, the most timely indicator), 0·92 (0·90 to 0·94; estimates of incidence generated after incorporating information about self-reported case status on the ZoeApp, which is a digital app), 0·67 (95% CI 0·60 to 0·73, emergency department attendances), 0·64 (95% CI 0·60 to 0·68, NHS 111 website visits), 0·63 (95% CI 0·56 to 0·69, wastewater viral genome concentrations), 0·60 (95% CI 0·52 to 0·66, admissions to hospital with positive COVID-19 status), 0·45 (95% CI 0·36 to 0·52, NHS 111 calls), 0·08 (95% CI -0·03 to 0·18, Google search rank for "covid"), -0·04 (95% CI -0·12 to 0·05, in-hours consultations with general practitioners), and -0·37 (95% CI -0·46 to -0·28, Google search rank for "coronavirus"). Time lags (-14 to +14 days) did not markedly improve these rho statistics. Clinical cases (the most timely indicator) captured a more consistent proportion of cases than the self-report digital app did.

INTERPRETATION

A suite of monitoring systems is useful. The household survey system was the most comprehensive and least biased epidemic monitor, but not very timely. Data from laboratory testing, the self-reporting digital app, and attendances to emergency departments were comparatively useful, fairly accurate, and timely epidemic trackers.

FUNDING

National Institute for Health and Care Research Health Protection Research Unit in Emergency Preparedness and Response, a partnership between the UK Health Security Agency, King's College London, and the University of East Anglia.

The transfer of environmental contaminants (Brominated and Chlorinated dioxins and biphenyls, PBDEs, HBCDDs, PCNs and PFAS) from recycled materials used for bedding to the eggs and tissues of chickens

Some types of poultry bedding made from recycled materials have been reported to contain environmental contaminants such as polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs, dioxins), polychlorinated biphenyls (PCBs) brominated flame retardants (BFRs) polychlorinated naphthalenes (PCNs), polybrominated dioxins (PBDD/Fs), perfluoroalkyl substances (PFAS), etc. In one of the first studies of its kind, the uptake of these contaminants by chicken muscle tissue, liver, and eggs from three types of recycled, commercially available bedding material was simultaneously investigated using conventional husbandry to raise day old chickens to maturity. A weight of evidence analysis showed that PCBs, polybrominated diphenylethers (PBDEs), PCDD/Fs, PCNs and PFAS displayed the highest potential for uptake which varied depending on the type of bedding material used. During the first three to four months of laying, an increasing trend was observed in the concentrations of ΣTEQ (summed toxic equivalence of PCDD/Fs, PCBs, PBDD/Fs, PCNs and polybrominated biphenyls), NDL-PCBs and PBDEs in the eggs of chickens raised on shredded cardboard. Further analysis using bio-transfer factors (BTFs) when egg production reached a steady state, revealed that some PCB congeners (PCBs 28, 81, 138, 153 and 180) irrespective of molecular configuration or chlorine number, showed the highest tendency for uptake. Conversely, BTFs for PBDEs showed good correlation with bromine number, increasing to a maximum value for BDE-209. This relationship was reversed for PCDFs (and to some extent for PCDDs) with tetra- and penta- chlorinated congeners showing a greater tendency for selective uptake. The overall patterns were consistent, although some variability in BTF values was observed between tested materials which may relate to differences in bioavailability. The results indicate a potentially overlooked source of food chain contamination as other livestock products (cow's milk, lamb, beef, duck, etc.) could be similarly impacted.

Climate warming and increasing Vibrio vulnificus infections in North America

Vibrio vulnificus is an opportunistic bacterial pathogen, occurring in warm low-salinity waters. V. vulnificus wound infections due to seawater exposure are infrequent but mortality rates are high (~ 18%). Seawater bacterial concentrations are increasing but changing disease pattern assessments or climate change projections are rare. Here, using a 30-year database of V. vulnificus cases for the Eastern USA, changing disease distribution was assessed. An ecological niche model was developed, trained and validated to identify links to oceanographic and climate data. This model was used to predict future disease distribution using data simulated by seven Global Climate Models (GCMs) which belong to the newest Coupled Model Intercomparison Project (CMIP6). Risk was estimated by calculating the total population within 200 km of the disease distribution. Predictions were generated for different "pathways" of global socioeconomic development which incorporate projections of greenhouse gas emissions and demographic change. In Eastern USA between 1988 and 2018, V. vulnificus wound infections increased eightfold (10-80 cases p.a.) and the northern case limit shifted northwards 48 km p.a. By 2041-2060, V. vulnificus infections may expand their current range to encompass major population centres around New York (40.7°N). Combined with a growing and increasingly elderly population, annual case numbers may double. By 2081-2100 V. vulnificus infections may be present in every Eastern USA State under medium-to-high future emissions and warming. The projected expansion of V. vulnificus wound infections stresses the need for increased individual and public health awareness in these areas.

Super-spreaders of novel coronaviruses that cause SARS, MERS and COVID-19: A systematic review

PURPOSE

Most index cases with novel coronavirus infections transmit disease to just one or two other individuals, but some individuals "super-spread"-they infect many secondary cases. Understanding common factors that super-spreaders may share could inform outbreak models, and be used to guide contact tracing during outbreaks.

METHODS

We searched in MEDLINE, Scopus, and preprints to identify studies about people documented as transmitting pathogens that cause SARS, MERS, or COVID-19 to at least nine other people. We extracted data to describe them by age, sex, location, occupation, activities, symptom severity, any underlying conditions, disease outcome and undertook quality assessment for outbreaks published by June 2021.

RESULTS

The most typical super-spreader was a male age 40+. Most SARS or MERS super-spreaders were very symptomatic, the super-spreading occurred in hospital settings and frequently the individual died. In contrast, COVID-19 super-spreaders often had very mild disease and most COVID-19 super-spreading happened in community settings.

CONCLUSIONS

SARS and MERS super-spreaders were often symptomatic, middle- or older-age adults who had a high mortality rate. In contrast, COVID-19 super-spreaders tended to have mild disease and were any adult age. More outbreak reports should be published with anonymized but useful demographic information to improve understanding of super-spreading, super-spreaders, and the settings in which super-spreading happens.

Risk perception from the consumption of untreated drinking water in a small island community

A small island community in Malaysia uses gravity-fed drinking water, and rejected water treatment by the authorities. This study was conducted to evaluate the community's risk perception towards their untreated water supply by interviewing one adult per household in four out of eight villages on the island. The survey asked questions on risk perception, socioeconomic characteristics, and perception of water supply quality. Water samples were collected from a total of 24 sampling locations across the four villages, and 91.7% of them were positive for E.coli. The study surveyed 218 households and found that 61.5% of respondents agreed to some degree that the water is safe to drink without treatment, while 67.9% of respondents disagreed to some degree that drinking tap water is associated with health risks, and 73.3% of respondents agreed to some degree that it is safe to drink directly from taps that are fitted with water filters. Using factor analysis to group the risk perception questions and multivariable GLM to explore relationships with underlying factors, the study found that older respondents, lower income level, positive water odour perception and positive water supply reliability perception lowers risk perception. The village of residence also significantly affects the risk perception level in the model.

Enhancing epidemiological surveillance of the emergence of the SARS-CoV-2 Omicron variant using spike gene target failure data, England, 15 November to 31 December 2021

When SARS-CoV-2 Omicron emerged in 2021, S gene target failure enabled differentiation between Omicron and the dominant Delta variant. In England, where S gene target surveillance (SGTS) was already established, this led to rapid identification (within ca 3 days of sample collection) of possible Omicron cases, alongside real-time surveillance and modelling of Omicron growth. SGTS was key to public health action (including case identification and incident management), and we share applied insights on how and when to use SGTS.

Community use of face masks and similar barriers to prevent respiratory illness such as COVID-19: a rapid scoping review

BackgroundEvidence for face-mask wearing in the community to protect against respiratory disease is unclear.AimTo assess effectiveness of wearing face masks in the community to prevent respiratory disease, and recommend improvements to this evidence base.MethodsWe systematically searched Scopus, Embase and MEDLINE for studies evaluating respiratory disease incidence after face-mask wearing (or not). Narrative synthesis and random-effects meta-analysis of attack rates for primary and secondary prevention were performed, subgrouped by design, setting, face barrier type, and who wore the mask. Preferred outcome was influenza-like illness. Grading of Recommendations, Assessment, Development and Evaluations (GRADE) quality assessment was undertaken and evidence base deficits described.Results33 studies (12 randomised control trials (RCTs)) were included. Mask wearing reduced primary infection by 6% (odds ratio (OR): 0.94; 95% CI: 0.75-1.19 for RCTs) to 61% (OR: 0.85; 95% CI: 0.32-2.27; OR: 0.39; 95% CI: 0.18-0.84 and OR: 0.61; 95% CI: 0.45-0.85 for cohort, case-control and cross-sectional studies respectively). RCTs suggested lowest secondary attack rates when both well and ill household members wore masks (OR: 0.81; 95% CI: 0.48-1.37). While RCTs might underestimate effects due to poor compliance and controls wearing masks, observational studies likely overestimate effects, as mask wearing might be associated with other risk-averse behaviours. GRADE was low or very low quality.ConclusionWearing face masks may reduce primary respiratory infection risk, probably by 6-15%. It is important to balance evidence from RCTs and observational studies when their conclusions widely differ and both are at risk of significant bias. COVID-19-specific studies are required.

Community use of face masks and similar barriers to prevent respiratory illness such as COVID-19: a rapid scoping review

BackgroundEvidence for face-mask wearing in the community to protect against respiratory disease is unclear.AimTo assess effectiveness of wearing face masks in the community to prevent respiratory disease, and recommend improvements to this evidence base.MethodsWe systematically searched Scopus, Embase and MEDLINE for studies evaluating respiratory disease incidence after face-mask wearing (or not). Narrative synthesis and random-effects meta-analysis of attack rates for primary and secondary prevention were performed, subgrouped by design, setting, face barrier type, and who wore the mask. Preferred outcome was influenza-like illness. Grading of Recommendations, Assessment, Development and Evaluations (GRADE) quality assessment was undertaken and evidence base deficits described.Results33 studies (12 randomised control trials (RCTs)) were included. Mask wearing reduced primary infection by 6% (odds ratio (OR): 0.94; 95% CI: 0.75-1.19 for RCTs) to 61% (OR: 0.85; 95% CI: 0.32-2.27; OR: 0.39; 95% CI: 0.18-0.84 and OR: 0.61; 95% CI: 0.45-0.85 for cohort, case-control and cross-sectional studies respectively). RCTs suggested lowest secondary attack rates when both well and ill household members wore masks (OR: 0.81; 95% CI: 0.48-1.37). While RCTs might underestimate effects due to poor compliance and controls wearing masks, observational studies likely overestimate effects, as mask wearing might be associated with other risk-averse behaviours. GRADE was low or very low quality.ConclusionWearing face masks may reduce primary respiratory infection risk, probably by 6-15%. It is important to balance evidence from RCTs and observational studies when their conclusions widely differ and both are at risk of significant bias. COVID-19-specific studies are required.

Demographic and socioeconomic patterns in healthcare-seeking behaviour for respiratory symptoms in England: a comparison with non-respiratory symptoms and between three healthcare services

OBJECTIVE

This study will analyse respiratory contacts to three healthcare services that capture more of the community disease burden than acute data sources, such as hospitalisations. The objective is to explore associations between contacts to these services and the patient's age, gender and deprivation. Results will be compared between healthcare services, and with non-respiratory contacts to explore how contacts differ by service and illness. It is crucial to investigate the sociodemographic patterns in healthcare-seeking behaviour to enable targeted public health interventions.

DESIGN

Ecological study.

SETTING

Surveillance of respiratory contacts to three healthcare services in England: telehealth helpline (NHS111); general practitioner in-hours (GPIH); and general practitioner out of hours unscheduled care (GPOOH).

PARTICIPANTS

13 million respiratory contacts to NHS111, GPIH and GPOOH.

OUTCOME MEASURES

Respiratory contacts to NHS111, GPIH and GPOOH, and non-respiratory contacts to NHS111 and GPOOH.

RESULTS

More respiratory contacts were observed for females, with 1.59, 1.73, and 1.95 times the rate of contacts to NHS111, GPOOH and GPIH, respectively. When compared with 15-44 year olds, there were 37.32, 18.66 and 6.21 times the rate of respiratory contacts to NHS111, GPOOH and GPIH in children <1 year. There were 1.75 and 2.70 times the rate of respiratory contacts in the most deprived areas compared with the least deprived to NHS111 and GPOOH. Elevated respiratory contacts were observed for males <5 years compared with females <5 years. Healthcare-seeking behaviours between respiratory and non-respiratory contacts were similar.

CONCLUSION

When contacts to services that capture more of the disease burden are explored, the demographic patterns are similar to those described in the literature for acute systems. Comparable results were observed between respiratory and non-respiratory contacts suggesting that when a wider spectrum of disease is explored, sociodemographic factors may be the strongest influencers of healthcare-seeking behaviour.

Comparison of statistical algorithms for daily syndromic surveillance aberration detection

Motivation

Public health authorities can provide more effective and timely interventions to protect populations during health events if they have effective multi-purpose surveillance systems. These systems rely on aberration detection algorithms to identify potential threats within large datasets. Ensuring the algorithms are sensitive, specific and timely is crucial for protecting public health. Here, we evaluate the performance of three detection algorithms extensively used for syndromic surveillance: the ‘rising activity, multilevel mixed effects, indicator emphasis’ (RAMMIE) method and the improved quasi-Poisson regression-based method known as ‘Farrington Flexible’ both currently used at Public Health England, and the ‘Early Aberration Reporting System’ (EARS) method used at the US Centre for Disease Control and Prevention. We model the wide range of data structures encountered within the daily syndromic surveillance systems used by PHE. We undertake extensive simulations to identify which algorithms work best across different types of syndromes and different outbreak sizes. We evaluate RAMMIE for the first time since its introduction. Performance metrics were computed and compared in the presence of a range of simulated outbreak types that were added to baseline data.

Results

We conclude that amongst the algorithm variants that have a high specificity (i.e. >90%), Farrington Flexible has the highest sensitivity and specificity, whereas RAMMIE has the highest probability of outbreak detection and is the most timely, typically detecting outbreaks 2–3 days earlier.

Availability and implementation

R codes developed for this project are available through https://github.com/FelipeJColon/AlgorithmComparison

Supplementary information

Supplementary data are available at Bioinformatics online.

Regional differences in presence of Shiga toxin-producing Escherichia coli virulence-associated genes in the environment in the North West and East Anglian regions of England

Shiga toxin-producing Escherichia coli is carried in the intestine of ruminant animals, and outbreaks have occurred after contact with ruminant animals or their environment. The presence of STEC virulence genes in the environment was investigated along recreational walking paths in the North West and East Anglia regions of England. In all, 720 boot sock samples from walkers' shoes were collected between April 2013 and July 2014. Multiplex PCR was used to detect E. coli based on the amplification of the uidA gene and investigate STEC-associated virulence genes eaeA, stx1 and stx2. The eaeA virulence gene was detected in 45·5% of the samples, where stx1 and/or stx2 was detected in 12·4% of samples. There was a difference between the two regions sampled, with the North West exhibiting a higher proportion of positive boot socks for stx compared to East Anglia. In univariate analysis, ground conditions, river flow and temperature were associated with positive boot socks. The detection of stx genes in the soil samples suggests that STEC is present in the English countryside and individuals may be at risk for infection after outdoor activities even if there is no direct contact with animals. SIGNIFICANCE AND IMPACT OF THE STUDY: Several outbreaks within the UK have highlighted the danger of contracting Shiga toxin-producing Escherichia coli from contact with areas recently vacated by livestock. This is more likely to occur for STEC infections compared to other zoonotic bacteria given the low infectious dose required. While studies have determined the prevalence of STEC within farms and petting zoos, determining the risk to individuals enjoying recreational outdoor activities that occur near where livestock may be present is less researched. This study describes the prevalence with which stx genes, indicative of STEC bacteria, were found in the environment in the English countryside.

Application of kernel smoothing to estimate the spatio-temporal variation in risk of STEC O157 in England

Identifying geographical areas with significantly higher or lower rates of infectious diseases can provide important aetiological clues to inform the development of public health policy and interventions designed to reduce morbidity. We applied kernel smoothing to estimate the spatial and spatio-temporal variation in risk of STEC O157 infection in England between 2009 and 2015, and to explore differences between the residential locations of cases reporting travel and those not reporting travel. We provide evidence that the distribution of STEC O157 infection in England is non-uniform with respect to the distribution of the at-risk population; that the spatial distribution of the three main genetic lineages infecting humans (I, II and I/II) differs significantly and that the spatio-temporal risk is highly dynamic. Our results also indicate that cases of STEC O157 reporting travel within or outside the UK are more likely to live in the south/south-east of the country, meaning that their residential location may not reflect the location of exposure that led to their infection. We suggest that the observed variation in risk reflects exposure to sources of STEC O157 that are geographically prescribed. These differences may be related to a combination of changes in the strains circulating in the ruminant reservoir, animal movements (livestock, birds or wildlife) or the behavior of individuals prior to infection. Further work to identify the importance of behaviours and exposures reported by cases relative to residential location is needed.

Ragweed pollen and allergic symptoms in children: Results from a three-year longitudinal study

Common ragweed is a highly allergenic invasive species in Europe, expected to become widespread under climate change. Allergy to ragweed manifests as eye, nasal and lung symptoms, and children may retain these throughout life. The dose-response relationship between symptoms and pollen concentrations is unclear. We undertook a longitudinal study, assessing the association between ragweed pollen concentration and allergic eye, nasal and lung symptoms in children living under a range of ragweed pollen concentrations in Croatia. Over three years, 85 children completed daily diaries, detailing allergic symptoms alongside daily location, activities and medication, resulting in 10,130 individual daily entries. The daily ragweed pollen concentration for the children's locations was obtained, alongside daily weather and air pollution. Parents completed a home/lifestyle/medical questionnaire. Generalised Additive Mixed Models established the relationship between pollen concentrations and symptoms, alongside other covariates. Eye symptoms were associated with mean daily pollen concentration over four days (day of symptoms plus 3 previous days); 61 grains/m³/day (95%CI: 45, 100) was the threshold at which 50% of children reported symptoms. Nasal symptoms were associated with mean daily pollen concentration over 12 days (day of symptoms plus 11 previous days); the threshold for 50% of children reporting symptoms was 40 grains/m³/day (95%CI: 24, 87). Lung symptoms showed a relationship with mean daily pollen concentration over 19 days (day of symptoms plus 18 previous days), with a threshold of 71 grains/m³/day (95%CI: 59, 88). Taking medication on the day of symptoms showed higher odds, suggesting responsive behaviour. Taking medication on the day prior to symptoms showed lower odds of reporting, indicating preventative behaviour. Different symptoms in children demonstrate varying dose-response relationships with ragweed pollen concentrations. Each symptom type responded to pollen exposure over different time periods. Using medication prior to symptoms can reduce symptom presence. These findings can be used to better manage paediatric ragweed allergy symptoms.

The potential of recycled materials used in agriculture to contaminate food through uptake by livestock

The potential for contaminant uptake from recycled materials used in livestock farming, to animal tissues and organs, was investigated in three practical modular studies involving broiler chickens, laying chickens and pigs. Six types of commercially available recycled materials were used either as bedding material for chickens or as fertilizer for cropland that later housed outdoor reared pigs. The contaminants studied included regulated contaminants e.g. polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs, dioxins) and polychlorinated biphenyls (PCBs), but related contaminants such as polybrominated diphenylethers (PBDEs), hexabrominated cyclododecane (HBCDD), polychlorinated naphthalenes (PCNs), polybrominated dioxins (PBDD/Fs) and perfluoroalkyl substances (PFAS) were also investigated. Contaminant occurrence in the recycled materials was verified prior to the studies and the relationship to tissue and egg concentrations in market ready animals was investigated using a weights of evidence approach. Contaminant uptake to animal tissues and eggs was observed in all the studies but the extent varied depending on the species and the recycled material. PCBs, PBDEs, PCDD/Fs, PCNs and PFAS showed the highest potential to transfer, with laying chickens showing the most pronounced effects. PBDD/Fs showed low concentrations in the recycled materials, making it difficult to evaluate potential transfer. Higher resulting occurrence levels in laying chickens relative to broilers suggests that period of contact with the materials may influence the extent of uptake in chickens. Bio-transfer factors (BTFs) estimated for PCDD/F and PCBs showed a greater magnitude for chicken muscle tissue relative to pigs with the highest values observed for PCBs in laying chickens. There were no significant differences between BTFs for the different chicken tissues which contrasted with the high BTF values for pigs liver relative to muscle. The study raises further questions which require investigation such as the effects of repeated or yearly application of recycled materials as fertilizers, and the batch homogeneity/consistency of available recycled materials.

Machine learning to refine decision making within a syndromic surveillance service

Background

Worldwide, syndromic surveillance is increasingly used for improved and timely situational awareness and early identification of public health threats. Syndromic data streams are fed into detection algorithms, which produce statistical alarms highlighting potential activity of public health importance. All alarms must be assessed to confirm whether they are of public health importance. In England, approximately 100 alarms are generated daily and, although their analysis is formalised through a risk assessment process, the process requires notable time, training, and maintenance of an expertise base to determine which alarms are of public health importance. The process is made more complicated by the observation that only 0.1% of statistical alarms are deemed to be of public health importance. Therefore, the aims of this study were to evaluate machine learning as a tool for computer-assisted human decision-making when assessing statistical alarms.

Methods

A record of the risk assessment process was obtained from Public Health England for all 67,505 statistical alarms between August 2013 and October 2015. This record contained information on the characteristics of the alarm (e.g. size, location). We used three Bayesian classifiers- naïve Bayes, tree-augmented naïve Bayes and Multinets - to examine the risk assessment record in England with respect to the final ‘Decision’ outcome made by an epidemiologist of ‘Alert’, ‘Monitor’ or ‘No-action’. Two further classifications based upon tree-augmented naïve Bayes and Multinets were implemented to account for the predominance of ‘No-action’ outcomes.

Results

The attributes of each individual risk assessment were linked to the final decision made by an epidemiologist, providing confidence in the current process. The naïve Bayesian classifier performed best, correctly classifying 51.5% of ‘Alert’ outcomes. If the ‘Alert’ and ‘Monitor’ actions are combined then performance increases to 82.6% correctly classified. We demonstrate how a decision support system based upon a naïve Bayes classifier could be operationalised within an operational syndromic surveillance system.

Conclusions

Within syndromic surveillance systems, machine learning techniques have the potential to make risk assessment following statistical alarms more automated, robust, and rigorous. However, our results also highlight the importance of specialist human input to the process.

Exploring Campylobacter seasonality across Europe using The European Surveillance System (TESSy), 2008 to 2016

BackgroundCampylobacteriosis is the most commonly reported food-borne infection in the European Union, with an annual number of cases estimated at around 9 million. In many countries, campylobacteriosis has a striking seasonal peak during early/mid-summer. In the early 2000s, several publications reported on campylobacteriosis seasonality across Europe and associations with temperature and precipitation. Subsequently, many European countries have introduced new measures against this food-borne disease.AimTo examine how the seasonality of campylobacteriosis varied across Europe from 2008-16, to explore associations with temperature and precipitation, and to compare these results with previous studies. We also sought to assess the utility of the European Surveillance System TESSy for cross-European seasonal analysis of campylobacteriosis.MethodsWard's Minimum Variance Clustering was used to group countries with similar seasonal patterns of campylobacteriosis. A two-stage multivariate meta-analysis methodology was used to explore associations with temperature and precipitation.ResultsNordic countries had a pronounced seasonal campylobacteriosis peak in mid- to late summer (weeks 29-32), while most other European countries had a less pronounced peak earlier in the year. The United Kingdom, Ireland, Hungary and Slovakia had a slightly earlier peak (week 24). Campylobacteriosis cases were positively associated with temperature and, to a lesser degree, precipitation.ConclusionAcross Europe, the strength and timing of campylobacteriosis peaks have remained similar to those observed previously. In addition, TESSy is a useful resource for cross-European seasonal analysis of infectious diseases such as campylobacteriosis, but its utility depends upon each country's reporting infrastructure.

Climate Change, Foodborne Pathogens and Illness in Higher-Income Countries

Purpose of Review

We present a review of the likely consequences of climate change for foodborne pathogens and associated human illness in higher-income countries.

Recent Findings

The relationships between climate and food are complex and hence the impacts of climate change uncertain. This makes it difficult to know which foodborne pathogens will be most affected, what the specific effects will be, and on what timescales changes might occur. Hence, a focus upon current capacity and adaptation potential against foodborne pathogens is essential. We highlight a number of developments that may enhance preparedness for climate change. These include the following:

Adoption of novel surveillance methods, such as syndromic methods, to speed up detection and increase the fidelity of intervention in foodborne outbreaks

Genotype-based approaches to surveillance of food pathogens to enhance spatiotemporal resolution in tracing and tracking of illness

Ever increasing integration of plant, animal and human surveillance systems, One Health, to maximise potential for identifying threats

Increased commitment to cross-border (global) information initiatives (including big data)

Improved clarity regarding the governance of complex societal issues such as the conflict between food safety and food waste

Strong user-centric (social) communications strategies to engage diverse stakeholder groups

Summary

The impact of climate change upon foodborne pathogens and associated illness is uncertain. This emphasises the need to enhance current capacity and adaptation potential against foodborne illness. A range of developments are explored in this paper to enhance preparedness.

Seasonality and the effects of weather on Campylobacter infections

Background

Campylobacteriosis is a major public health concern. The weather factors that influence spatial and seasonal distributions are not fully understood.

Methods

To investigate the impacts of temperature and rainfall on Campylobacter infections in England and Wales, cases of Campylobacter were linked to local temperature and rainfall at laboratory postcodes in the 30 days before the specimen date. Methods for investigation included a comparative conditional incidence, wavelet, clustering, and time series analyses.

Results

The increase of Campylobacter infections in the late spring was significantly linked to temperature two weeks before, with an increase in conditional incidence of 0.175 cases per 100,000 per week for weeks 17 to 24; the relationship to temperature was not linear. Generalized structural time series model revealed that changes in temperature accounted for 33.3% of the expected cases of Campylobacteriosis, with an indication of the direction and relevant temperature range. Wavelet analysis showed a strong annual cycle with additional harmonics at four and six months. Cluster analysis showed three clusters of seasonality with geographic similarities representing metropolitan, rural, and other areas.

Conclusions

The association of Campylobacteriosis with temperature is likely to be indirect. High-resolution spatial temporal linkage of weather parameters and cases is important in improving weather associations with infectious diseases. The primary driver of Campylobacter incidence remains to be determined; other avenues, such as insect contamination of chicken flocks through poor biosecurity should be explored.

Electronic supplementary material

The online version of this article (10.1186/s12879-019-3840-7) contains supplementary material, which is available to authorized users.

Erratum: "Climate Change and Future Pollen Allergy in Europe"

[This corrects the article DOI: 10.1289/EHP173.].

Modifiable Risk Factors for Common Ragweed (Ambrosia artemisiifolia) Allergy and Disease in Children: A Case-Control Study

Ragweed allergy is a major public health concern. Within Europe, ragweed is an introduced species and research has indicated that the amounts of ragweed pollen are likely to increase over Europe due to climate change, with corresponding increases in ragweed allergy. To address this threat, improving our understanding of predisposing factors for allergic sensitisation to ragweed and disease is necessary, specifically focusing upon factors that are potentially modifiable (i.e., environmental). In this study, a total of 4013 children aged 2–13 years were recruited across Croatia to undergo skin prick tests to determine sensitisation to ragweed and other aeroallergens. A parental questionnaire collected home environment, lifestyle, family and personal medical history, and socioeconomic information. Environmental variables were obtained using Geographical Information Systems and data from nearby pollen, weather, and air pollution stations. Logistic regression was performed (clustered on school) focusing on risk factors for allergic sensitisation and disease. Ragweed sensitisation was strongly associated with ragweed pollen at levels over 5000 grains m^–3 year⁻¹ and, above these levels, the risk of sensitisation was 12–16 times greater than in low pollen areas with about 400 grains m^–3 year⁻¹. Genetic factors were strongly associated with sensitisation but nearly all potentially modifiable factors were insignificant. This included measures of local land use and proximity to potential sources of ragweed pollen. Rural residence was protective (odds ratio (OR) 0.73, 95% confidence interval (CI) 0.55–0.98), but the factors underlying this association were unclear. Being sensitised to ragweed doubled (OR 2.17, 95% CI 1.59–2.96) the risk of rhinoconjunctivitis. No other potentially modifiable risk factors were associated with rhinoconjunctivitis. Ragweed sensitisation was strongly associated with ragweed pollen, and sensitisation was significantly associated with rhinoconjunctivitis. Apart from ragweed pollen levels, few other potentially modifiable factors were significantly associated with ragweed sensitisation. Hence, strategies to lower the risk of sensitisation should focus upon ragweed control.

The influence of a major sporting event upon emergency department attendances; A retrospective cross-national European study

Major sporting events may influence attendance levels at hospital emergency departments (ED). Previous research has focussed on the impact of single games, or wins/losses for specific teams/countries, limiting wider generalisations. Here we explore the impact of the Euro 2016 football championships on ED attendances across four participating nations (England, France, Northern Ireland, Wales), using a single methodology. Match days were found to have no significant impact upon daily ED attendances levels. Focussing upon hourly attendances, ED attendances across all countries in the four hour pre-match period were statistically significantly lower than would be expected (OR 0.97, 95% CI 0.94-0.99) and further reduced during matches (OR 0.94, 95% CI 0.91-0.97). In the 4 hour post-match period there was no significant increase in attendances (OR 1.01, 95% CI 0.99-1.04). However, these impacts were highly variable between individual matches: for example in the 4 hour period following the final, involving France, the number of ED attendances in France increased significantly (OR 1.27, 95% CI 1.13-1.42). Overall our results indicate relatively small impacts of major sporting events upon ED attendances. The heterogeneity observed makes it difficult for health providers to predict how major sporting events may affect ED attendances but supports the future development of compatible systems in different countries to support cross-border public health surveillance.

A methodological framework for the evaluation of syndromic surveillance systems: a case study of England

BACKGROUND

Syndromic surveillance complements traditional public health surveillance by collecting and analysing health indicators in near real time. The rationale of syndromic surveillance is that it may detect health threats faster than traditional surveillance systems permitting more timely, and hence potentially more effective public health action. The effectiveness of syndromic surveillance largely relies on the methods used to detect aberrations. Very few studies have evaluated the performance of syndromic surveillance systems and consequently little is known about the types of events that such systems can and cannot detect.

METHODS

We introduce a framework for the evaluation of syndromic surveillance systems that can be used in any setting based upon the use of simulated scenarios. For a range of scenarios this allows the time and probability of detection to be determined and uncertainty is fully incorporated. In addition, we demonstrate how such a framework can model the benefits of increases in the number of centres reporting syndromic data and also determine the minimum size of outbreaks that can or cannot be detected. Here, we demonstrate its utility using simulations of national influenza outbreaks and localised outbreaks of cryptosporidiosis.

RESULTS

Influenza outbreaks are consistently detected with larger outbreaks being detected in a more timely manner. Small cryptosporidiosis outbreaks (<1000 symptomatic individuals) are unlikely to be detected. We also demonstrate the advantages of having multiple syndromic data streams (e.g. emergency attendance data, telephone helpline data, general practice consultation data) as different streams are able to detect different outbreak types with different efficacy (e.g. emergency attendance data are useful for the detection of pandemic influenza but not for outbreaks of cryptosporidiosis). We also highlight that for any one disease, the utility of data streams may vary geographically, and that the detection ability of syndromic surveillance varies seasonally (e.g. an influenza outbreak starting in July is detected sooner than one starting later in the year). We argue that our framework constitutes a useful tool for public health emergency preparedness in multiple settings.

CONCLUSIONS

The proposed framework allows the exhaustive evaluation of any syndromic surveillance system and constitutes a useful tool for emergency preparedness and response.

Food-borne disease and climate change in the United Kingdom

This review examined the likely impact of climate change upon food-borne disease in the UK using Campylobacter and Salmonella as example organisms. Campylobacter is an important food-borne disease and an increasing public health threat. There is a reasonable evidence base that the environment and weather play a role in its transmission to humans. However, uncertainty as to the precise mechanisms through which weather affects disease, make it difficult to assess the likely impact of climate change. There are strong positive associations between Salmonella cases and ambient temperature, and a clear understanding of the mechanisms behind this. However, because the incidence of Salmonella disease is declining in the UK, any climate change increases are likely to be small. For both Salmonella and Campylobacter the disease incidence is greatest in older adults and young children. There are many pathways through which climate change may affect food but only a few of these have been rigorously examined. This provides a high degree of uncertainty as to what the impacts of climate change will be. Food is highly controlled at the National and EU level. This provides the UK with resilience to climate change as well as potential to adapt to its consequences but it is unknown whether these are sufficient in the context of a changing climate.

After the epidemic: Zika virus projections for Latin America and the Caribbean

Background

Zika is one of the most challenging emergent vector-borne diseases, yet its future public health impact remains unclear. Zika was of little public health concern until recent reports of its association with congenital syndromes. By 3 August 2017 ∼217,000 Zika cases and ∼3,400 cases of associated congenital syndrome were reported in Latin America and the Caribbean. Some modelling exercises suggest that Zika virus infection could become endemic in agreement with recent declarations from the The World Health Organisation.

Methodology/Principal findings

We produced high-resolution spatially-explicit projections of Zika cases, associated congenital syndromes and monetary costs for Latin America and the Caribbean now that the epidemic phase of the disease appears to be over. In contrast to previous studies which have adopted a modelling approach to map Zika potential, we project case numbers using a statistical approach based upon reported dengue case data as a Zika surrogate. Our results indicate that ∼12.3 (0.7–162.3) million Zika cases could be expected across Latin America and the Caribbean every year, leading to ∼64.4 (0.2–5159.3) thousand cases of Guillain-Barré syndrome and ∼4.7 (0.0–116.3) thousand cases of microcephaly. The economic burden of these neurological sequelae are estimated to be USD ∼2.3 (USD 0–159.3) billion per annum.

Conclusions/Significance

Zika is likely to have significant public health consequences across Latin America and the Caribbean in years to come. Our projections inform regional and federal health authorities, offering an opportunity to adapt to this public health challenge.

In February 2016 the World Health Organisation (WHO) declared Zika virus infection in the Americas as a Public Health Emergency of International Concern (PHEIC). By November 2016, Zika was declared a long-term public health challenge. This change of status implies that Zika is likely to become an endemic problem in the region. Due to the PHEIC status of Zika, most current research has rightly focused on the epidemic stage of the disease; however, it is timely and critical to consider the public health consequences after such epidemic phase. We used one of the largest and most spatially diverse panels of epidemiological surveillance data comprising 12 years of dengue case observations from Brazil and Mexico, and covering an area of over ten million km². State-of-the-art statistical models, and high-resolution (0.5 × 0.5 degrees) climate and demographic data were used to produce spatially-explicit projections of Zika infection for Latin America and the Caribbean. Model projections were then used to estimate the number of cases with neurological sequelae and their economic cost. Our findings indicate that the potential health and economic burden of Zika could be considerably large for the region should it become endemic. The estimated burden of Zika under an endemic state highlights the need for health authorities in the countries at risk to promote preventive and control measures.

Novel Sampling Method for Assessing Human-Pathogen Interactions in the Natural Environment Using Boot Socks and Citizen Scientists, with Application to Campylobacter Seasonality

This paper introduces a novel method for sampling pathogens in natural environments. It uses fabric boot socks worn over walkers' shoes to allow the collection of composite samples over large areas. Wide-area sampling is better suited to studies focusing on human exposure to pathogens (e.g., recreational walking). This sampling method is implemented using a citizen science approach: groups of three walkers wearing boot socks undertook one of six routes, 40 times over 16 months in the North West (NW) and East Anglian (EA) regions of England. To validate this methodology, we report the successful implementation of this citizen science approach, the observation that Campylobacter bacteria were detected on 47% of boot socks, and the observation that multiple boot socks from individual walks produced consistent results. The findings indicate higher Campylobacter levels in the livestock-dominated NW than in EA (55.8% versus 38.6%). Seasonal differences in the presence of Campylobacter bacteria were found between the regions, with indications of winter peaks in both regions but a spring peak in the NW. The presence of Campylobacter bacteria on boot socks was negatively associated with ambient temperature (P = 0.011) and positively associated with precipitation (P < 0.001), results consistent with our understanding of Campylobacter survival and the probability of material adhering to boot socks. Campylobacter jejuni was the predominant species found; Campylobacter coli was largely restricted to the livestock-dominated NW. Source attribution analysis indicated that the potential source of C. jejuni was predominantly sheep in the NW and wild birds in EA but did not differ between peak and nonpeak periods of human incidence.IMPORTANCE There is debate in the literature on the pathways through which pathogens are transferred from the environment to humans. We report on the success of a novel method for sampling human-pathogen interactions using boot socks and citizen science techniques, which enable us to sample human-pathogen interactions that may occur through visits to natural environments. This contrasts with traditional environmental sampling, which is based on spot sampling techniques and does not sample human-pathogen interactions. Our methods are of practical value to scientists trying to understand the transmission of pathogens from the environment to people. Our findings provide insight into the risk of Campylobacter exposure from recreational visits and an understanding of seasonal differences in risk and the factors behind these patterns. We highlight the Campylobacter species predominantly encountered and the potential sources of C. jejuni.

Climate Change and Future Pollen Allergy in Europe

BACKGROUND

Globally, pollen allergy is a major public health problem, but a fundamental unknown is the likely impact of climate change. To our knowledge, this is the first study to quantify the consequences of climate change upon pollen allergy in humans.

OBJECTIVES

We produced quantitative estimates of the potential impact of climate change upon pollen allergy in humans, focusing upon common ragweed (Ambrosia artemisiifolia) in Europe.

METHODS

A process-based model estimated the change in ragweed's range under climate change. A second model simulated current and future ragweed pollen levels. These findings were translated into health burdens using a dose-response curve generated from a systematic review and from current and future population data. Models considered two different suites of regional climate/pollen models, two greenhouse gas emissions scenarios [Representative Concentration Pathways (RCPs) 4.5 and 8.5], and three different plant invasion scenarios.

RESULTS

Our primary estimates indicated that sensitization to ragweed will more than double in Europe, from 33 to 77 million people, by 2041-2060. According to our projections, sensitization will increase in countries with an existing ragweed problem (e.g., Hungary, the Balkans), but the greatest proportional increases will occur where sensitization is uncommon (e.g., Germany, Poland, France). Higher pollen concentrations and a longer pollen season may also increase the severity of symptoms. Our model projections were driven predominantly by changes in climate (66%) but were also influenced by current trends in the spread of this invasive plant species. Assumptions about the rate at which ragweed spreads throughout Europe had a large influence upon the results.

CONCLUSIONS

Our quantitative estimates indicate that ragweed pollen allergy will become a common health problem across Europe, expanding into areas where it is currently uncommon. Control of ragweed spread may be an important adaptation strategy in response to climate change. Citation: Lake IR, Jones NR, Agnew M, Goodess CM, Giorgi F, Hamaoui-Laguel L, Semenov MA, Solomon F, Storkey J, Vautard R, Epstein MM. 2017. Climate change and future pollen allergy in Europe. Environ Health Perspect 125:385-391; http://dx.doi.org/10.1289/EHP173.

Improving Land Compensation Procedures via Gis and Hedonic Pricing

One of the results of new road construction is often a reduction in the price of nearby properties. In the United Kingdom property owners can be compensated for this loss through the Land Compensation Act. The appropriate level of compensation is currently determined by valuers and is mainly based upon their expertise and skill. This study aims to determine what the correct level of compensation should be. It has been specifically designed to fulfil the requirements of current legislation and can be integrated into existing compensation procedures. This was achieved through a hedonic pricing study that relates current property prices to a wide range of factors. These variables include the structure, neighbourhood, accessibility, and environment of the property, in addition to the impact of nearby roads. These were all created through GIS and large-scale digital data. The study, which is based on over 3500 property sales in Glasgow, Scotland, suggests that property prices were depressed by 0.202% for each decibel increase in road noise. This result has enabled a more streamlined compensation procedure to be developed and demonstrates that compensation claims can be estimated at the road-development stage. This would allow any compensation claims to be assessed prior to road construction and inform the design of noise-reduction measures.

The effects of flooding on dioxin and PCB levels in food produced on industrial river catchments

This research examined the effect of regular flooding upon PCDD/F and PCB levels in milk, beef and lamb, produced on the floodplains of industrial river catchments. Our unique dataset included more than 200 samples analysed for PCDD/Fs and PCBs over two data collection phases (1998-1999 & 2008-2010) from working farms. A robust paired study design was adopted with samples taken from flood-prone farms and nearby control farms not subject to flooding. On industrial river catchments regular flooding is associated with higher PCDD/F and PCB levels in soils and grass. This contamination may be transferred to food but the impact varied by food type. These contrasts may be due to physiological differences between animals, the ages at which they are sent to market and differences in animal husbandry. To minimise the risks of producing food on flood-prone land in industrial river catchments, as well as on any land with elevated PCDD/F and PCB levels, this research suggests a number of options. The choice of livestock may be important and as an example in our study beef cattle accumulated PCDD/Fs to a higher degree than sheep. Land management may also play a role and could include minimising the time that livestock spend on such land or feeding commercial feed, low in PCDD/Fs and PCBs, where appropriate.

The effects of river flooding on dioxin and PCBs in beef

In 2008-2010, samples of meat from 40 beef cattle, along with grass, soil and commercial feed, taken from ten matched pairs of flood-prone and control farms, were analysed for PCDD/Fs and PCBs. Concentrations were higher in soil and grass from flood-prone farms. The beef samples from flood-prone farms had total TEQ levels about 20% higher than on control farms. A majority of flood-prone farms (7/10) had higher median levels in beef than on the corresponding control farm. This first controlled investigation into PCDD/F and PCB contamination in beef produced on flood-prone land, presents robust evidence that flooding is a contaminant transfer mechanism to cattle raised on river catchments with a history of urbanisation and industrialisation. PCDD/F and PCB sources in these river systems are likely to be a result of the legacy of contamination from previous industrialisation, as well as more recent combustion activity or pollution events.

Climate change and the emergence of vector-borne diseases in Europe: case study of dengue fever

BACKGROUND

Dengue fever is the most prevalent mosquito-borne viral disease worldwide. Dengue transmission is critically dependent on climatic factors and there is much concern as to whether climate change would spread the disease to areas currently unaffected. The occurrence of autochthonous infections in Croatia and France in 2010 has raised concerns about a potential re-emergence of dengue in Europe. The objective of this study is to estimate dengue risk in Europe under climate change scenarios.

METHODS

We used a Generalized Additive Model (GAM) to estimate dengue fever risk as a function of climatic variables (maximum temperature, minimum temperature, precipitation, humidity) and socioeconomic factors (population density, urbanisation, GDP per capita and population size), under contemporary conditions (1985-2007) in Mexico. We then used our model estimates to project dengue incidence under baseline conditions (1961-1990) and three climate change scenarios: short-term 2011-2040, medium-term 2041-2070 and long-term 2071-2100 across Europe. The model was used to calculate average number of yearly dengue cases at a spatial resolution of 10 × 10 km grid covering all land surface of the currently 27 EU member states. To our knowledge, this is the first attempt to model dengue fever risk in Europe in terms of disease occurrence rather than mosquito presence.

RESULTS

The results were presented using Geographical Information System (GIS) and allowed identification of areas at high risk. Dengue fever hot spots were clustered around the coastal areas of the Mediterranean and Adriatic seas and the Po Valley in northern Italy.

CONCLUSIONS

This risk assessment study is likely to be a valuable tool assisting effective and targeted adaptation responses to reduce the likely increased burden of dengue fever in a warmer world.

The effects of weather and climate change on dengue

Background

There is much uncertainty about the future impact of climate change on vector-borne diseases. Such uncertainty reflects the difficulties in modelling the complex interactions between disease, climatic and socioeconomic determinants. We used a comprehensive panel dataset from Mexico covering 23 years of province-specific dengue reports across nine climatic regions to estimate the impact of weather on dengue, accounting for the effects of non-climatic factors.

Methods and Findings

Using a Generalized Additive Model, we estimated statistically significant effects of weather and access to piped water on dengue. The effects of weather were highly nonlinear. Minimum temperature (Tmin) had almost no effect on dengue incidence below 5°C, but Tmin values above 18°C showed a rapidly increasing effect. Maximum temperature above 20°C also showed an increasing effect on dengue incidence with a peak around 32°C, after which the effect declined. There is also an increasing effect of precipitation as it rose to about 550 mm, beyond which such effect declines. Rising access to piped water was related to increasing dengue incidence. We used our model estimations to project the potential impact of climate change on dengue incidence under three emission scenarios by 2030, 2050, and 2080. An increase of up to 40% in dengue incidence by 2080 was estimated under climate change while holding the other driving factors constant.

Conclusions

Our results indicate that weather significantly influences dengue incidence in Mexico and that such relationships are highly nonlinear. These findings highlight the importance of using flexible model specifications when analysing weather–health interactions. Climate change may contribute to an increase in dengue incidence. Rising access to piped water may aggravate dengue incidence if it leads to increased domestic water storage. Climate change may therefore influence the success or failure of future efforts against dengue.

Relationships between weather and mosquito-borne diseases are nonlinear in nature. This means that the number of disease cases does not vary equally with changes in the climate system. Identifying adequately the form of the relationship between disease outcomes and their drivers in an empirical fashion can be tedious and imprecise. Here, we use a statistical modelling approach that estimates the form of the relationships between dengue and weather in an automated way. We use this approach to analyse a comprehensive dataset covering 23 years of dengue reports from Mexico. Our model incorporates the effects of some non-climatic factors that are key for disease occurrence. We then use our estimations to project the potential impact of climate change on dengue incidence under three different scenarios for three different time periods. The estimated effects of weather on dengue were highly nonlinear. These results highlight the importance of using flexible modelling approaches for the analysis of disease-weather relationships with a nonlinear behaviour. Rising access to water supply was related to increases in dengue incidence. This situation may be related to increased water storage induced by unreliable water supply. Dengue incidence may increase to about 40% by 2080 due to climate change. This increase in dengue incidence may be aggravated by a rising access to piped water if it leads to domestic water storage, although any adaptation measures to rising dengue may also affect the risk. Our results contribute to a better overall understanding of the epidemiology of dengue.

The combined impact of rural residence and socio-economic status on premature mortality

The health of rural and urban populations differs, with rural areas appearing healthier. However, it is unknown whether the benefit of living in rural areas is felt by individuals in all levels of deprivation, or whether some suffer a disadvantage of rural residence. For England and Wales 2001-2003 premature mortality rates were calculated, subdivided by individual deprivation and gender, for areas with differing rurality characteristics. Premature mortality data (age 50-retirement) and a measure of the individual's deprivation (National Statistics Socio-economic Classification 1-7) was obtained from death certificates. Overall premature mortality was examined as well as premature mortality subdivided by major cause. Male premature mortality rates (age 50-64) fell with increasing rurality for individuals in all socio-economic status classifications. The most deprived individuals benefitted most from residence in increasingly rural areas. Similar trends were observed when premature mortality was subdivided by the major causes of death. Female premature mortality rates (age 50-59) demonstrated similar trends but the differences between urban and rural areas were less marked.

Seasonal variations in the levels of PCDD/Fs, PCBs and PBDEs in cows' milk

The first detailed investigation into seasonal variations in PCDD/F, PCB and PBDE concentrations in cows' milk from individual farms was conducted. From August 2009 milk samples were taken at 6 weeks intervals from the bulk tank of 2 farms over a period of one year. Samples of dietary inputs including commercial feed, grass, silage and soil were also collected at 6 weekly intervals from each farm. Detailed animal husbandry information was additionally obtained. For all these samples total TEQ, ∑ICES6 and the ∑7 PBDE congeners was calculated. The results demonstrated that the concentrations of these sets of compounds fluctuate notably over short periods in cows' milk. This variability was such that the highest observed concentrations were nearly double the lowest concentrations detected for both PCDD/Fs and PCBs and PBDEs. Fluctuations between extremes were observed over time periods as short as 6 weeks. Some, but not all, of these variations may be explained by changes in the contaminant concentrations of dietary inputs consumed by the cattle. Changes in contaminant inputs from grass and silage were identified as being the most important source of these fluctuations. Given this variability, the results from PCDD/F and PCB and PBDE monitoring studies may be highly dependent upon when the individual samples were taken. The results have important implications for total diet studies and sampling design.

Climate change and food security: health impacts in developed countries

BACKGROUND

Anthropogenic climate change will affect global food production, with uncertain consequences for human health in developed countries.

OBJECTIVES

We investigated the potential impact of climate change on food security (nutrition and food safety) and the implications for human health in developed countries.

METHODS

Expert input and structured literature searches were conducted and synthesized to produce overall assessments of the likely impacts of climate change on global food production and recommendations for future research and policy changes.

RESULTS

Increasing food prices may lower the nutritional quality of dietary intakes, exacerbate obesity, and amplify health inequalities. Altered conditions for food production may result in emerging pathogens, new crop and livestock species, and altered use of pesticides and veterinary medicines, and affect the main transfer mechanisms through which contaminants move from the environment into food. All these have implications for food safety and the nutritional content of food. Climate change mitigation may increase consumption of foods whose production reduces greenhouse gas emissions. Impacts may include reduced red meat consumption (with positive effects on saturated fat, but negative impacts on zinc and iron intake) and reduced winter fruit and vegetable consumption. Developed countries have complex structures in place that may be used to adapt to the food safety consequences of climate change, although their effectiveness will vary between countries, and the ability to respond to nutritional challenges is less certain.

CONCLUSIONS

Climate change will have notable impacts upon nutrition and food safety in developed countries, but further research is necessary to accurately quantify these impacts. Uncertainty about future impacts, coupled with evidence that climate change may lead to more variable food quality, emphasizes the need to maintain and strengthen existing structures and policies to regulate food production, monitor food quality and safety, and respond to nutritional and safety issues that arise.

Climate change and food security: health impacts in developed countries

BACKGROUND

Anthropogenic climate change will affect global food production, with uncertain consequences for human health in developed countries.

OBJECTIVES

We investigated the potential impact of climate change on food security (nutrition and food safety) and the implications for human health in developed countries.

METHODS

Expert input and structured literature searches were conducted and synthesized to produce overall assessments of the likely impacts of climate change on global food production and recommendations for future research and policy changes.

RESULTS

Increasing food prices may lower the nutritional quality of dietary intakes, exacerbate obesity, and amplify health inequalities. Altered conditions for food production may result in emerging pathogens, new crop and livestock species, and altered use of pesticides and veterinary medicines, and affect the main transfer mechanisms through which contaminants move from the environment into food. All these have implications for food safety and the nutritional content of food. Climate change mitigation may increase consumption of foods whose production reduces greenhouse gas emissions. Impacts may include reduced red meat consumption (with positive effects on saturated fat, but negative impacts on zinc and iron intake) and reduced winter fruit and vegetable consumption. Developed countries have complex structures in place that may be used to adapt to the food safety consequences of climate change, although their effectiveness will vary between countries, and the ability to respond to nutritional challenges is less certain.

CONCLUSIONS

Climate change will have notable impacts upon nutrition and food safety in developed countries, but further research is necessary to accurately quantify these impacts. Uncertainty about future impacts, coupled with evidence that climate change may lead to more variable food quality, emphasizes the need to maintain and strengthen existing structures and policies to regulate food production, monitor food quality and safety, and respond to nutritional and safety issues that arise.

Climate variability and dengue fever in warm and humid Mexico

Multiple linear regression models were fitted to look for associations between changes in the incidence rate of dengue fever and climate variability in the warm and humid region of Mexico. Data were collected for 12 Mexican provinces over a 23-year period (January 1985 to December 2007). Our results show that the incidence rate or risk of infection is higher during El Niño events and in the warm and wet season. We provide evidence to show that dengue fever incidence was positively associated with the strength of El Niño and the minimum temperature, especially during the cool and dry season. Our study complements the understanding of dengue fever dynamics in the region and may be useful for the development of early warning systems.

Effects of river flooding on polybrominated diphenyl ether (PBDE) levels in cows' milk, soil, and grass

The first investigation into PBDE levels in food produced from flood-prone land on industrial river catchments was conducted. In August 2008 samples of cows' milk, along with grass and soil were taken from 5 pairs of flood-prone and control farms on the River Trent (Central UK). The sum of 7 BDE congeners (28, 47, 99, 100, 153, 154, and 183) was calculated. Higher PBDE levels occurred in soil on flood-prone compared to control farms (median 770 vs 280 ng/kg dry weight). These higher levels were not reflected in the grass samples indicating that PBDE contamination on soils is not transferred efficiently to grass. This observation alongside the fact that cows on flood-prone farms spend time on non-flood-prone land and are fed substantial quantities of commercial feed are reasons why higher PBDE levels were not found in milk from flood-prone farms (median 300 vs 250 ng/kg fat weight). Similar BDE47/BDE99 ratios were observed in soil and grass samples compared to the PBDE product commonly used in the UK, indicating few differences in source-pathway transfer efficiencies between congeners. The BDE47/BDE99 ratio in the milk samples was greater than those in the grass and feed indicating differential food to milk transfer efficiencies between congeners.

Effect of water hardness on cardiovascular mortality: an ecological time series approach

BACKGROUND

Numerous studies have suggested an inverse relationship between drinking water hardness and cardiovascular disease. However, the weight of evidence is insufficient for the WHO to implement a health-based guideline for water hardness. This study followed WHO recommendations to assess the feasibility of using ecological time series data from areas exposed to step changes in water hardness to investigate this issue.

METHOD

Monthly time series of cardiovascular mortality data, subdivided by age and sex, were systematically collected from areas reported to have undergone step changes in water hardness, calcium and magnesium in England and Wales between 1981 and 2005. Time series methods were used to investigate the effect of water hardness changes on mortality.

RESULTS

No evidence was found of an association between step changes in drinking water hardness or drinking water calcium and cardiovascular mortality. The lack of areas with large populations and a reasonable change in magnesium levels precludes a definitive conclusion about the impact of this cation. We use our results on the variability of the series to consider the data requirements (size of population, time of water hardness change) for such a study to have sufficient power. Only data from areas with large populations (>500,000) are likely to be able to detect a change of the size suggested by previous studies (rate ratio of 1.06).

CONCLUSION

Ecological time series studies of populations exposed to changes in drinking water hardness may not be able to provide conclusive evidence on the links between water hardness and cardiovascular mortality unless very large populations are studied. Investigations of individuals may be more informative.

Microbiological surveillance of private water supplies in England: the impact of environmental and climate factors on water quality

A passive surveillance system captured information on 34,904 microbiological samples from 11,233 private drinking water supplies within England as well as the associated constructional, climatic and environmental variables. Escherichia coli was detected in 6588 (18.87%) of samples and at least one positive sample was detected from 3638 (32.39%) of sites. However, this estimate of supplies failing to meet the European drinking water E. coli standard was probably an underestimate as the more samples taken per supply, the more likely the supply was to fail. A multivariable model of private water supplies data showed a strong seasonal impact, with samples between January and May being significantly less contaminated with E. coli than samples between June and December. Samples from springs (OR 2.5, CI 2.0-3.1) or surface waters (OR 2.4, CI 0.8-7.0) were more likely to fail than groundwater sources, as were supplies with no effective treatment (OR1.8, CI 1.5-2.3). Commercial supplies were less likely to fail than domestic supplies (OR 0.63, CI 0.48-0.83) and the probability of failure was linearly associated with the density of sheep in the area and rainfall on the previous day. A Monte Carlo modelling approach was used to estimate that, had sufficient samples been taken, 54% (95% confidence intervals 49-59%) of all private water supplies in England were likely to be unsatisfactory. These findings will be able to inform risk assessments of private water supplies prior to microbiological results being available.

A systematic review of analytical observational studies investigating the association between cardiovascular disease and drinking water hardness

The aim of this study is to systematically review and critically assess analytical observational epidemiology studies investigating the association between levels of drinking water hardness and cardiovascular disease. We searched electronic databases and used standardised forms to extract data and assess study quality. Of 2,906 papers identified, 14 met the inclusion criteria (nine case control and five cohort studies). Of the nine case control studies, seven examined both drinking water magnesium and calcium and risk of death from cardiovascular disease. A pooled odds ratio showed a statistically significant inverse association between magnesium and cardiovascular mortality (OR 0.75 (95%CI 0.68, 0.82), p < 0.001). Only two studies reported a statistically significant effect for calcium. Substantial heterogeneity between studies made calculation of a summary estimate for drinking water calcium inappropriate. Of three cohort studies reviewed, two were of good quality. A weak suggestion that soft water was harmful in females and possibly associated with a slightly greater risk of sudden death was reported, but there was no association between water hardness and mortality from stroke or cardiovascular disease. This study found significant evidence of an inverse association between magnesium levels in drinking water and cardiovascular mortality following a meta-analysis of case control studies. Evidence for calcium remains unclear.

The influence of road curvature on fatal crashes in New Zealand

Bends in roads can cause crashes but a recent study in the UK found that areas with mostly curved roads had lower crash rates than areas with straighter roads. This present study aimed to replicate the previous research in a different country. Variations in the number of fatal road crashes occurring between 1996 and 2005 in 73 territorial local authorities across New Zealand were modelled against possible predictors. The predictors were traffic flow, population counts and characteristics, car use, socio-economic deprivation, climate, altitude and road characteristics including four measures of average road curvature. The best predictors of the number of fatal crashes on urban roads, rural state highways and other rural roads were traffic flow, speed limitation and socio-economic deprivation. Holding significant factors constant, there was no evidence that TLAs with the most curved roads had more crashes than elsewhere. Fatal crashes on urban roads were significantly and negatively related to two measures of road curvature: the ratio of road length to straight distance and the cumulative angle turned per kilometre. Weaker negative associations on rural state highways could have occurred by chance. These results offer limited support to the suggestion that frequently occurring road bends might be protective.

Case-control study of environmental and social factors influencing cryptosporidiosis

We report on the first case-control study to investigate the role of wider environmental and socioeconomic factors upon human cryptosporidiosis. Using GIS the detailed locations of 3368 laboratory-confirmed cases were compared to the locations of an equal number of controls. All cases were genotyped enabling Cryptosporidium hominis and Cryptosporidium parvum to be examined separately. When all cryptosporidiosis cases were analyzed, several location variables were strongly associated with illness: areas with many higher socioeconomic status individuals, many individuals aged less than 4 years, areas with a high estimate of Cryptosporidium applied to land from manure, and areas with poorer water treatment. For C. hominis cases, the strongly significant risk factors were areas with many higher socioeconomic status individuals, areas with many young children and urban areas. Socioeconomic status and areas with many individuals aged less then 4 years had a greater impact for infection with C. hominis than for C. parvum. Policy implications are discussed.