Our study plans to quantify the effect of higher temperatures on different critical Turkish health outcomes mainly to chart future developments and to identify locations in Turkey that may be potential vulnerable hotspots. The general structure of the temperature mortality function was estimated with different fixed-level effects, with a specific focus on the mortality effect of maximum apparent temperature. Regional models were fitted to pinpoint the thresholds where the temperature–mortality relation changes, thus investigating whether the thresholds are determined nationally or regionally. The future patterns were estimated by extrapolating from future temperature trends: analyzing possible future mortality trends under the restricting assumption of minimal acclimation. Using the fixed effect regression structure, social and developmental variables acting as heat effect modifiers were also identified. In the largest dataset, the initial fixed effect regression specification supports the hypothesis summarized by the U-shaped relationship between temperature and mortality. This is a first corroboration for Turkish climate and health research. In addition, intermediation effects were substantiated for the level of urbanization and population density, and the human development and health development within provinces. Regional heterogeneity is substantiated by the mortality–temperature relationship and the significant threshold deviations from the national average.

During the first months of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) epidemic in 2020, Spain implemented an initial lockdown period on 15 March followed by a strengthened lockdown period on 30 March when only essential workers continued to commute to work. However, little is known about the epidemic dynamics in different age groups during these periods.

We used the daily number of coronavirus 2019 cases (by date of symptom onset) reported to the National Epidemiological Surveillance Network among individuals aged 15–19 years through 65–69 years. For each age group g, we computed the proportion PrE(g) of individuals in age group g among all reported cases aged 15–69 years during the pre-lockdown period (1−10 March 2020) and the corresponding proportion PrL(g) during two lockdown periods (initial: 25 March−3 April; strengthened: 8–17 April 2020). For each lockdown period, we computed the proportion ratios PR(g) = PrL(g)/PrE(g). For each pair of age groups g1, g2, PR(g1)>PR(g2) implies a relative increase in the incidence of detected SARS-CoV-2 infection in the age group g1 compared with g2 for the lockdown period vs. the pre-lockdown period.

For the initial lockdown period, the highest PR values were in age groups 50–54 years (PR = 1.21; 95% CI: 1.12,1.30) and 55–59 years (PR = 1.19; 1.11,1.27). For the second lockdown period, the highest PR values were in age groups 15–19 years (PR = 1.26; 0.95,1.68) and 50–54 years (PR = 1.20; 1.09,1.31).

Our results suggest that different outbreak control measures led to different changes in the relative incidence by age group. During the initial lockdown period, when non-essential work was allowed, individuals aged 40–64 years, particularly those aged 50–59 years, had a higher relative incidence compared with the pre-lockdown period. Younger adults/older adolescents had an increased relative incidence during the later, strengthened lockdown. The role of different age groups during the epidemic should be considered when implementing future mitigation efforts.

There is limited information on the roles of different age groups in propagating pertussis outbreaks, and the temporal changes in those roles since the introduction of acellular pertussis vaccines. The relative roles of different age groups in propagating the 2010 and the 2014 pertussis epidemics in California were evaluated using the relative risk (RR) statistic that measures the change in the group's proportion among all detected cases before vs. after the epidemic peak. For the 2010–11 epidemic, evidence for a predominant transmission age group was weak, with the largest RR estimates being 1.26 (95% CI 1.08–1.46) (aged 11–13 years); 1.19 (1.01–1.4) (aged 9–10 years); 1.17 (0.86–1.59) (aged 14–15 years); 1.12 (0.86–1.46) (aged 16–19 years) and 1.1 (0.89–1.36) (aged 7–8 years). The 2014 epidemic showed a strong signal of the role of older adolescents, with the highest RR estimate being in those aged 14–15 years (RR = 1.83, 1.61–2.07), followed by adolescents aged 16–19 years (RR = 1.41, 1.24–1.61) and 11–13 years (RR = 1.26, 1.12–1.41), with lower RR estimates in other age groups. As the time following introduction of acellular pertussis vaccines in California progressed, older adolescents played an increasing role in transmission during the major pertussis outbreaks. Booster pertussis vaccination for older adolescents with vaccines effective against pertussis transmission should be considered with the aim of mitigating future pertussis epidemics in the community.

Dengue presents a wide clinical spectrum of signs and symptoms, with characteristics of the host potentially influencing the disease evolution. Therefore, the purpose of this study was to evaluate the influence of gender and age on dengue clinical outcomes in a recent outbreak situation in Brazil, applying a cross-sectional design and including 6703 dengue cases with laboratory confirmation, occurring in Vitória, Espírito Santo State, Brazil, between 2007 and 2013. Data were obtained from the Information System for Notifiable Diseases. Overall, 11·3% of the sample presented with severe dengue, which affected 13·0% of males, 10·0% of females, 8·8% of children, 12·5% of adolescents, 10·5% of adults and 15·5% of the elderly. Age was higher in the severe dengue group (P = 0·03). Severe dengue was associated with males and the elderly (P < 0·01); however, considering only severe cases, children presented haemorrhage and plasma leakage more frequently than older age groups. The results emphasize the importance of a differentiated protocol for management of dengue cases, taking into consideration host factors like age. These findings also suggest the elderly and children as priority groups for immunization in a future implementation of a vaccine.

We sought to systematically review the published literature describing the epidemiological aspects of the first wave of pandemic A(H1N1) 2009 influenza in the Southern Hemisphere. Fifteen studies were included in this review, originating from South America, Australia or New Zealand, and Africa. Across the different studies, 16·8–45·3% of the laboratory-confirmed cases were admitted to hospital, and 7·5–26·0% of these cases were admitted to intensive care units (ICUs). The fatality rate was 0·5–1·5% for laboratory-confirmed cases in 6/8 studies reporting specific relevant data, and 14·3–22·2% for cases admitted to ICUs in 5/7 studies, respectively. In 4/5 studies the majority of laboratory-confirmed cases were observed in young and middle-aged adults, the percentage of older adults increased the higher the level of healthcare the cases received (e.g. laboratory confirmation, hospitalization or ICU admission) or for fatal cases. Many of the cases had no prior comorbidity, including conditions identified as risk factors for seasonal influenza. Pregnant women represented 7·4–9·1% and 7·1–9·1% of unselected laboratory-confirmed cases and of those admitted to ICUs, respectively. Obesity and morbid obesity were more commonly reported as the level of healthcare increased.

This study aimed to compare systematically approaches to estimating influenza-attributable mortality in older Australians. Using monthly age-specific death data together with viral surveillance counts for influenza and respiratory syncytial virus, we explored two of the most frequently used methods of estimating excess influenza-attributable disease: Poisson and Serfling regression models. These approaches produced consistent age and temporal patterns in estimates of influenza-attributable mortality in older Australians but some variation in the magnitude of the disease burden. Of Australians aged >50 years, average annual estimated influenza-attributable deaths (all cause) ranged from 2314 to 3457 for the Serfling and Poisson regression models, respectively. The excess influenza-attributable disease burden was substantial under all approaches.

Three age groups of Bulinus natalensis, immature, mature but not yet egg-laying and mature egg-laying, were infected with miracidia of Schistosoma margrebowiei. The growth of infected, exposed but showing no signs of infection, and uninfected control groups, were examined at weekly intervals for ten weeks post exposure. Snails exposed to infection when immature, even in the group where no patent development ensued, showed a statistically significant reduction in growth and this was evident as early as 2–5 weeks post exposure. When infection occurred at the stage prior to egg-laying a significant reduction in growth was seen but only in the group which developed a patent infection. This was also the case for the egg-laying group although the reduction in growth was only significant in the final three weeks of the experiment. Thus in all three age groups, growth rate was reduced and the infected snails were significantly smaller at the end of ten weeks compared with the controls. The reasons for these effects are discussed.

Objectives: The aim of this study was to examine the influence of participants' characteristics on the results produced by formal consensus methods.

Methods: The approach was an experimental study of 346 participants in 20 groups rating the appropriateness of four mental health interventions for the treatment of chronic fatigue syndrome, irritable bowel syndrome, and chronic back pain. There were four factors in the design: systematic literature review provided or not, decisions made under realistic or “ideal” resource assumptions, clinically mixed (general practitioners and mental health professionals) or homogenous group (general practitioners only), convened or mail-only group. A group's rating was defined as the median of participants' ratings. The influence of participants' characteristics (age, sex, and specialty) was examined using multilevel models.

Results: The largest differences were between the GPs and mental health professionals, both in their initial ratings of the different interventions, and in how much they altered their ratings between rounds. There were smaller but statistically significant (p<.05) differences between specialty and age groups in initial ratings for the treatment (by whatever means) of different conditions, and for certain conditions women increased their ratings more than men. Women rated intervention more favorably when assuming “ideal” rather than realistic levels of resources, but men did not.

Conclusions: Our findings support the practice of treating professional specialty as an important determinant of the results in consensus panels.

Procedures for continuous adjustment of lamb birth and weaning weights for effects of ewe age were developed using 18 747 birth and 13 139 weaning weight records of Polypay sheep enrolled in the US National Sheep Improvement Program. Changes in birth and weaning weights across ewe age groups were modelled using hybrid curves that combined asymptotic regression models to describe initial increases in lamb weight as ewes moved into adulthood with secondorder polynomials to describe declines in lamb weights in older ewes. Lamb birth and weaning weights were highest (and the asymptotic and polynomial forms comprising the hybrid curves intersected) at ewe ages of 76 and 52 months, respectively. Across all ewe ages, hybrid curves were superior to second- and third-order polynomials in goodness of fit, producing a parabolic form with a flat top and different decay rates on either side of the ewe ages corresponding to maximum lamb weights. Fourth- and fifth-degree polynomials were equivalent to hybrid curves in goodness of fit, but generally did not produce reasonable predictions for the oldest ewes. Adjustment factors derived from the hybrid curve predicted that lamb birth weight would increase from 76% of maximum in 11-month-old ewes to 90 and 96% of maximum in 24- and 36-month-old ewes, respectively, and then decline to 97% of maximum at 105 months. For weaning weight, 83, 95, 99, and 93% of maximum lamb weight were attained at ewe ages of 11, 24, 36, and 105 months, respectively. Resulting multiplicative adjustment factors avoid discontinuities at boundaries between ewe age categories and are particularly useful in accelerated or other multiple-season lambing systems.