Seasonal Patterns Of Mortality Research Articles

National trends in pediatric drowning - insights from the Israeli Ministry of Health registry-based cohort.

Pediatric drowning is a persistent public health concern in Israel, with distinct seasonal, regional, age-specific, and sex-specific patterns in incidence and mortality. This study underscores the need for a comprehensive prevention strategy that includes year-round public education, environmental safety measures, and targeted interventions for high-risk groups to reduce drowning incidents and fatalities among children effectively. • Pediatric drowning represents a significant public health challenge globally, with varying rates. • In Israel, pediatric drowning is the second leading cause of death from all injury-related deaths. Thus far, the measures and interventions to reduce fatalities were not proven effective enough. • Pediatric drowning in Israel, with a 9% mortality rate, revealed a biphasic rate varied by sex and is higher in coastal regions and during winter and spring. • There was a notable increase in drowning incidents during the last 3 years of the study period (2020-2022), coinciding with the COVID-19 pandemic.

Moose and white‐tailed deer mortality peaks in fall and late winter

AbstractThe Grand Portage Band of Lake Superior Chippewa manages for sustainable subsistence harvests of moose (mooz; Alces alces) and white‐tailed deer (waawaashkeshi; Odocoileus virginianus). Moose populations in northern Minnesota, USA, are declining, which may necessitate alterations to Indigenous subsistence practices. Moose and deer exhibit seasonal behaviors such as altered space use and movement strategies, to which gray wolves (ma'iingan; Canis lupus) and humans may adapt, resulting in seasonal mortality patterns. Identifying periods of increased moose and deer vulnerability is important for achieving tribal conservation objectives. We assessed seasonal cause‐specific mortality of adult moose (2010–2021) and deer (2016–2022) fitted with global positioning system collars on and near the Grand Portage Indian Reservation (Gichi Onigaming; GPIR) in Minnesota and hypothesized mortality risk would be influenced by species‐specific space use patterns and weather. We estimated survival rates and mortality risk using time‐to‐event models. We recorded 42 moose mortalities (17 health issues, 8 predations, 4 subsistence harvests, 13 unknown causes) and 49 deer mortalities (26 predations, 13 harvests, 4 other causes, 6 unknown causes). Mean annual moose survival was 83.2%, and mortality risk peaked during late winter (~25 April) and fall (~8 October). Mean annual deer survival was 48.0%, and mortality risk peaked during late winter (~25 March) and during their fall migration period (~11 November). Mortality timing coincided with transitions between space use states (i.e., periods of spatial stability), suggesting ungulates are at greater risk during these transitional periods, though movement strategy (i.e., resident vs. migratory) did not influence mortality risk. Further, increased winter severity corresponded with increased deer mortality. We observed similar temporal peaks in mortality risk when harvest mortalities were censored, suggesting our observed seasonal mortality peaks occur naturally despite harvest comprising most fall deer mortality. Our results can inform population models and harvest regulations by identifying periods of mortality risk on GPIR under Anishinaabe principles of seventh‐generation conservation planning.

Post-settlement dynamics of Japanese flounder Paralichthys olivaceus in Tango Bay: Seasonal patterns in growth, mortality, and recruitment potential.

Japanese flounder Paralichthys olivaceus is one of the most valuable coastal flatfish species in East Asia. To investigate post-settlement growth and mortality, juveniles were sampled in Tango Bay (Japan) weekly throughout the settlement period in 2007 and 2008. Otolith (lapillus) microstructure analysis enabled the categorization of juveniles into six biweekly cohorts each year. Later cohorts exhibited higher growth rates possibly because of higher water temperatures. A key observation was the direct relationship between high mortality and high density in mid-season cohorts in both years, pointing to density-dependent mortality. This increased mortality may be attributed to predation, including cannibalism by earlier cohorts. Furthermore, growth-selective mortality was evident soon after settlement, underscoring the vulnerability of slow growers to predation during the early juvenile stage. Although earlier and later cohorts were less abundant but showed promising recruitment potential, the prospective contribution of mid-season cohorts to the adult population remained uncertain. The results clearly highlight the importance of density-dependent mortality in population regulation in post-settlement Japanese flounder.

Month-to-month all-cause mortality forecasting: a method allowing for changes in seasonal patterns.

Forecasting of seasonal mortality patterns can provide useful information for planning health-care demand and capacity. Timely mortality forecasts are needed during severe winter spikes and/or pandemic waves to guide policy-making and public health decisions. In this article, we propose a flexible method for forecasting all-cause mortality in real time considering short-term changes in seasonal patterns within an epidemiologic year. All-cause mortality data have the advantage of being available with less delay than cause-specific mortality data. In this study, we use all-cause monthly death counts obtained from the national statistical offices of Denmark, France, Spain, and Sweden from epidemic seasons 2012-2013 through 2021-2022 to demonstrate the performance of the proposed approach. The method forecasts deaths 1 month ahead, based on their expected ratio to the next month. Prediction intervals are obtained via bootstrapping. The forecasts accurately predict the winter mortality peaks before the COVID-19 pandemic. Although the method predicts mortality less accurately during the first wave of the COVID-19 pandemic, it captures the aspects of later waves better than other traditional methods. The method is attractive for health researchers and governmental offices for aiding public health responses because it uses minimal input data, makes simple and intuitive assumptions, and provides accurate forecasts both during seasonal influenza epidemics and during novel virus pandemics.

Temporal, seasonal, and spatial patterns in fall-related mortality in Japan: Analysis of national vital statistics from 1975 to 2019

BackgroundFalls are a significant public health issue in aging societies. This study aimed to examine the temporal, seasonal, and spatial patterns in fall-related mortality in Japan, and to investigate the potential factors associated with fall-related mortality. MethodsThe number of unintentional fall-related deaths from 1979 to 2019 were obtained from Japanese vital statistics and crude and direct age-standardized mortality rates (DSR) were calculated. We also calculated the standardized mortality ratio (SMR) to determine seasonal and prefectural differences. In addition, spatial regression was conducted to examine the potential factors associated with fall-related mortality. ResultsThe DSR among those over 65 years old showed a decreasing trend from 1979, but remained unchanged from 1990 to 2019. Based on the spatial regression model, the factors significantly associated with SMRs were the proportion of the aged population (Coefficient: 0.049), the number of hospitals (0.118), the number of clinics (1.169), the number of hospital beds (-0.060), and the number of physiotherapists (-0.069) for men; and the proportion of aged single households (-0.060), the number of hospitals (0.132), the number of clinics (1.498), the number of hospital beds (-0.051), and the number of physicians (-0.308) for women. ConclusionsFall-related mortality among Japanese elderly people has remained unchanged in recent years. In addition, seasonal and spatial patterns were also observed, and it was found that demographic data and healthcare resources in the prefectures affected fall-related mortality rates. Appropriate prevention measures of fall-related deaths should be considered according to the region-specific characteristics and issues.

Survival and cause-specific mortality in adult females of a northern migratory ungulate

Survival of ungulates can vary seasonally due to changing environmental conditions, e.g. weather or predation pressure. The wild forest reindeer (Rangifer tarandus fennicus, “WFR”) migrate between calving and wintering grounds. The annual cycle of female WFR includes four main seasons (wintering, calving, rutting and autumn migration) during which they are subject to different conditions, but almost nothing is known about their survival or mortality patterns. We measured survival in 305 GPS-tagged female WFR in two subpopulations in Finland (2010–2022). Data were analysed for inter-annual and seasonal patterns in survival and cause-specific mortality (predation, traffic, accidents and unknown causes) with known-fate models. Inter-annual survival in Suomenselkä (mean 0.90) showed an increasing trend during the study and was higher than in Kainuu (mean 0.84) which showed a declining trend. Seasonal variation in survival was population dependent. Survival was lowest in Kainuu during the winter while in Suomenselkä, it was lowest during autumn migration. Concerning cause-specific mortality, seasonal variation mirrored variation in predation that was the primary cause of mortality (55% of cases). Wolves (Canis lupus) killed the majority of predated individuals (58%). Predation rates were two times higher in Kainuu where the wolf density was higher. We provide the first adult survival estimates for WFR and show that the seasonal variation in survival is clearly different between these two northern ungulate populations. This indicates that seasonal variation in survival is determined by site-dependent factors and cannot be generalised across populations.

Seasonal and spatial patterns of mortality and socio-economic characteristics associated with exposure to air pollution and a lack of green areas

Seasonal and spatial patterns of mortality and socio-economic characteristics associated with exposure to air pollution and a lack of green areas

An ensemble learning strategy for panel time series forecasting of excess mortality during the COVID-19 pandemic

Quantifying and analyzing excess mortality in crises such as the ongoing COVID-19 pandemic is crucial for policymakers. Traditional measures fail to take into account differences in the level, long-term secular trends, and seasonal patterns in all-cause mortality across countries and regions. This paper develops and empirically investigates the forecasting performance of a novel, flexible and dynamic ensemble learning with a model selection strategy (DELMS) for the seasonal time series forecasting of monthly respiratory disease death data across a pool of 61 heterogeneous countries. The strategy is based on a Bayesian model averaging (BMA) of heterogeneous time series methods involving both the selection of the subset of best forecasters (model confidence set), the identification of the best holdout period for each contributed model, and the determination of optimal weights using out-of-sample predictive accuracy. A model selection strategy is also developed to remove the outlier models and to combine the models with reasonable accuracy in the ensemble. The empirical outcomes of this large set of experiments show that the accuracy of the BMA approach is significantly improved with DELMS when selecting a flexible and dynamic holdout period and removing the outlier models. Additionally, the forecasts of respiratory disease deaths for each country are highly accurate and exhibit a high correlation (94%) with COVID-19 deaths in 2020.

Temporal dynamics of fine root production, mortality and turnover deviate across branch orders in a larch stand.

Fine roots play a key role in carbon, nutrient, and water biogeochemical cycles in forest ecosystems. However, inter-annual dynamics of fine root production, mortality, and turnover on the basis of long-term measurement have been less studied. Here, field scanning rhizotrons were employed for tracking fine root by branch order over a 6years period in a larch plantation. For total fine roots, from the first- to the fifth-order roots, annual root length production, length mortality, standing crops, and turnover rate varied up to 3.4, 2.3, 1.5, and 2.3-folds during the study period, respectively. The inter-annual variability of those roots indices in the first-order and the second-order roots were greater than that of the higher order (third- to fifth-order) roots. The turnover rate was markedly larger for the first-order roots than for the higher order roots, showing the greatest variability up to 20times. Seasonal dynamics of root length production followed a general concentrated pattern with peak typically occurring in June or July, whereas root length mortality followed a general bimodal mortality pattern with the dominant peak in May and the secondary peak in August or October. Furthermore, the seasonal patterns of root length production and mortality were similar across years, especially for the first-order and the second-order roots. These results from long-term observation were beneficial for reducing uncertainty of characterizing fine root demography in consideration of large variation among years. Our findings highlight it is important for better understanding of fine root dynamics and determining root demography through distinguishing observation years and root branch orders.

Amphibian and Reptile Road Mortality in Special Nature Reserve Obedska Bara, Serbia.

Simple SummaryRoad networks allow for faster and easier transportation of people and goods, but unfortunately, they also have many negative effects on nature. For example, due to vehicle collisions, millions of animals are killed or injured every year. Usually, the effects of road mortality are not equally distributed in time and space. The main aim of this study was to examine patterns of amphibian and reptile road mortality on the road near the largest wetland in Serbia, on the edge of the Special Nature Reserve “Obedska bara”. During the 32 fieldwork days in 2018, we found more than 20,000 road-killed amphibians and reptiles, with amphibians accounting for 93% and reptiles 7% of the total fatalities. The numbers of killed amphibians and reptiles were not uniform between different habitat types and seasons. Therefore, an examination of the temporal (hot moments—periods when mortality rates are highest) and spatial patterns (hotspots—road sections with a higher concentration of vehicle collision) of roadkill is necessary for applying effective mitigation measures, which can reduce the negative impact of traffic.Amphibians and reptiles are the most threatened vertebrates by traffic, especially near ponds and wetlands. The main aim of this study was to examine seasonal and spatial patterns of amphibian and reptile road mortality in Special Nature Reserve “Obedska bara” (Serbia). We chose a road section of 4.2 km near the largest wetland in Serbia, with two different habitat types (forest-pond and agricultural area-pond). During 2018 (32 fieldwork days) and 2019–2020 (three control fieldwork days), we found 20,457 and 2231 road-killed animals, respectively. We recorded nine amphibian and eight reptile species. Amphibians (93%) were more vulnerable to traffic than reptiles (7%). The number of killed amphibians and reptiles varied between the seasons. Generally, amphibian roadkill was most frequent during the summer, whereas reptile roadkill was most frequent in spring and at the end of the summer. Furthermore, different roadkill patterns were observed during the examined months. In addition, we found that habitat type significantly affects the vulnerability of animals towards the roads. For both amphibians and reptiles, there were significant aggregations of roadkill, and most hotspots were located at the forest pond habitat type where mitigation measures must be applied (construction of tunnels and fences).

Wild Predators, Livestock, and Free Ranging Dogs: Patterns of Livestock Mortality and Attitudes of People Toward Predators in an Urbanizing Trans-Himalayan Landscape

Livestock depredation by large carnivores is a significant source of conflicts over predators and an important conservation and economic concern. Preventing livestock loss to wild predators is a substantial focus of human-carnivore conflict mitigation programs. A key assumption of the preventive strategy is reduction in the livestock losses leading to a positive shift in the attitudes toward predators. Therefore, it is important to quantify the true extent of livestock mortality caused by wild predators and its influence on attitudes of the affected communities. We examined seasonal and spatial patterns of livestock mortality and factors influencing people's attitudes toward wild predators i.e., snow leopards (Panthera uncia) and wolves (Canis lupuschanco) and free-ranging dogs (Canis lupusfamiliaris) in a Trans-Himalayan urbanizing landscape in India. We used systematic sampling to select the survey households and implemented a semi-structured questionnaire to respondents. The sampled villages (n= 16) represent a mosaic of urban and agricultural ecosystems within a radius of 40 km of Leh town. In 2016–2017, 93% of the sampled households lost livestock to predators, accounting for 0.93 animals per household per year. However, of the total events of livestock mortality, 33% were because of weather/natural events, 24% by snow leopards, 20% because of disease, 15% because of free-ranging dogs and 9% because of wolves. The annual economic loss per household because of livestock mortality was USD 371, a substantial loss given the average per capita income of USD 270 in the region. Of the total loss, weather/natural events caused highest loss of USD 131 (35%), followed by snow leopards USD 91 (25%), disease USD 87 (24%), free ranging dogs USD 48 (13%), and wolves USD 14 (4%). Despite losing a considerable proportion of livestock (33 %) to wild predators, respondents showed a positive attitude toward them but exhibited neutral attitudes toward free-ranging dogs. Gender emerged as the most important determinant of attitudes toward wild predators, with men showing higher positive attitude score toward wild predators than women. Our findings highlight the context specific variation in human-wildlife interactions and emphasize that generalizations must be avoided in the absence of site specific evidence.

Year-round monitoring at a Pacific coastal campus reveals similar winter and spring collision mortality and high vulnerability of the Varied Thrush

Abstract Bird–window collisions are a leading cause of direct anthropogenic avian mortality, yet our state of knowledge regarding this threat relies heavily on eastern North American studies. Seasonal patterns of collision mortality may differ along the Pacific coast, and western North American species remain understudied. We therefore surveyed a stratified random sample of 8 buildings for collisions at the University of British Columbia, Vancouver, Canada over 45-day periods during 2 winters, 1 spring, 1 summer, and 1 fall season between January 22, 2015 and March 15, 2017. After accounting for the rate of scavenging and efficiency of observers in finding carcasses, we estimated that 360 collision fatalities (95% CI: 281–486) occurred over 225 days of collision monitoring. Collision mortality was highest in fall, but in contrast to most published research, collision mortality was intermediate in both winter and spring and was lowest in summer. In winter 2017, we performed point-count surveys to assess whether individual species are disproportionately vulnerable to collisions when accounting for population size and found that the Varied Thrush (Ixoreus naevius) was 76.9 times more likely to collide with buildings, relative to average species vulnerability in winter. To our knowledge, this is the first study to report the Varied Thrush as a species that is disproportionately vulnerable to collisions. Further studies are needed to assess the vulnerability of Western North American species and subspecies, and to determine whether similar patterns of seasonal collision mortality are found elsewhere.

Estimates of mortality attributable to COVID-19: a statistical model for monitoring COVID-19 and seasonal influenza, Denmark, spring 2020.

BackgroundTimely monitoring of COVID-19 impact on mortality is critical for rapid risk assessment and public health action.AimBuilding upon well-established models to estimate influenza-related mortality, we propose a new statistical Attributable Mortality Model (AttMOMO), which estimates mortality attributable to one or more pathogens simultaneously (e.g. SARS-CoV-2 and seasonal influenza viruses), while adjusting for seasonality and excess temperatures.MethodsData from Nationwide Danish registers from 2014-week(W)W27 to 2020-W22 were used to exemplify utilities of the model, and to estimate COVID-19 and influenza attributable mortality from 2019-W40 to 2020-W20.ResultsSARS-CoV-2 was registered in Denmark from 2020-W09. Mortality attributable to COVID-19 in Denmark increased steeply, and peaked in 2020-W14. As preventive measures and national lockdown were implemented from 2020-W12, the attributable mortality started declining within a few weeks. Mortality attributable to COVID-19 from 2020-W09 to 2020-W20 was estimated to 16.2 (95% confidence interval (CI): 12.0 to 20.4) per 100,000 person-years. The 2019/20 influenza season was mild with few deaths attributable to influenza, 3.2 (95% CI: 1.1 to 5.4) per 100,000 person-years.ConclusionAttMOMO estimates mortality attributable to several pathogens simultaneously, providing a fuller picture of mortality by COVID-19 during the pandemic in the context of other seasonal diseases and mortality patterns. Using Danish data, we show that the model accurately estimates mortality attributable to COVID-19 and influenza, respectively. We propose using standardised indicators for pathogen circulation in the population, to make estimates comparable between countries and applicable for timely monitoring.

'Big Data' and Parish Registers: a Case Study of Mortality in Early Modern Non-Metropolitan Surrey

This article uses aggregate analysis of parish registers to consider mortality in the early modern period. Based on a case study of the majority of the historical county of Surrey between about 1550 and 1750, it explores the nature and geographical distribution of mortality crises and seasonal patterns of mortality in normal, non-crisis, times. For the former it focusses mainly on two crises only a few years apart but with different causes, the dearth of the late 1590s and an outbreak of plague in 1603.

Sezonowe wahania umieralności w wybranych państwach Europy Środkowo-Wschodniej i Zachodniej

The report concerns analysis of seasonal patterns of mortality for selected countries of Central and Eastern Europe, compared with France, Italy and Germany, based on monthly Eurostat data from 1999 to 2019. In the literature it is known that increase of mortality rates in winter is typical for the North Hemisphere. We show that there are similarities and differences in the pattern – both in the averages and volatility – of this increase in particular countries. To this aim the , and seasonality measures, known in the literature, were applied. The results are visualized in graphical and tabular form. In addition, significance of this seasonal variation is tested based on the regression with binary seasonal variables.

Shift in proximate causes of mortality for six large migratory raptors over a century

Delayed maturity and low reproductive rate make raptors naturally sensitive to high mortality rates, yet a wide variety of human-related threats negatively affect their population dynamics and persistence over time. We modelled the variability in the proximate causes of mortality associated with six species of large migratory raptors characterized by different ecological traits. We tested the hypothesis that species-specific mortality signals occur owing to differential exposure to threats in space and time. We relied on an unprecedently large dataset of ring (band) recovery (31,269 records) over a period of >100 years. Our findings suggested that mortality of these birds has declined dramatically since the late 1970s. We found species-specific seasonal patterns of mortality, with higher mortality rates during early life-stages. For Black Kite, Common Buzzard, and Osprey, mortality increased with distance travelled and decreased with distance from migratory bottlenecks. Human-related mortality was higher than natural mortality (47% vs 5.6%), but after 1979 indirect anthropogenic factors increased, while direct ones decreased. Raptors showed differential specific exposure to mortality causes (direct human: Honey Buzzard, Marsh Harrier; indirect human: Common Buzzard, Black Kite; direct and indirect human: Osprey; natural: Montagu's Harrier). Conservation efforts and international laws have helped lower mortality caused directly by humans, but new emerging human-related threats are impacting migratory raptors and call for advanced conservation efforts. In a fast-changing world, anticipating future threats is key to stemming losses and boosting future preservation.

Impact of the COVID-19 on the Seasonal Mortality Pattern in Spain: Unexpected Change in Trend as an Objective and Early Marker of Health Alert

Background: The first death by COVID-19 in Spain was on February 13th However, on that precise date the tracking of positive cases of infection was mainly limited to subjects at high risk of contagion The aim of this study was to determine whether unexpected changes in trend of the all-cause mortality curve, could serve as an indicator to provide early preventive interventions Method: To analyze all-cause mortality data a Poisson distribution was selected with a Log function The goodness of fit statistics was studied, and both the predicted value of mean of response and residual were obtained For daily mortality, a seasonal decomposition was performed by weighted moving averages method Finding: The results showed a constantly increasing risk from the ninth week (Sunday 23 rd February) Three weeks before lockdown Adjusted RR: 0·403 (Week 8), 0·406 (W9), 0·408 (W10), 0·446 (W11), 0·583 (W12), P 0·001 in all cases In males the risk increased from the same week Adjusted RR: 0·372 (W8), 0·386 (W9), 0·388 (W10), 0·429 (W11), 0·578 (W12), P0·001 In contrast, for females the risk started to increase from week 11 By groups of age there were again two weeks of difference between the population under 65 years (W 11) vs over 74 years of age (W 9) Six days were earned using baseline years with similar seasonal trend pattern Interpretation: Facing an unknown viral process, epidemiological surveillance must pay attention to subtle modifications of seasonal trend patterns to take appropriate preventive measures as early as possible

Elderly mortality at the Russian Far East: seasonality and mitigation

In many countries of the world, demographic changes have occurred, characterized by an increase in the share of socially inactive elderly people. The goal is a medical and demographic analysis of the elderly in the Far East. For Khabarovsk and Birobidzhan, seasonal patterns of mortality and self-preserving behavior of older people were investigated. In order to determine the actions and personal attitudes of self-preserving behavior for the prevention of cardiovascular diseases, elderly people who visited the Vertical fitness center in Birobidzhan were interviewed. It was found that the overall mortality rate among older people is higher among men than among women. The main causes of death are cardiovascular diseases, which have a pronounced seasonality with a maximum in winter. It is shown that 23% of men and 48% of women do not demonstrate high social and physical activity and do not have any skills to maintain their health.

Changes in historical typhoid transmission across 16 U.S. cities, 1889-1931: Quantifying the impact of investments in water and sewer infrastructures.

Investments in water and sanitation systems are believed to have led to the decline in typhoid fever in developed countries, such that most cases now occur in regions lacking adequate clean water and sanitation. Exploring seasonal and long-term patterns in historical typhoid mortality in the United States can offer deeper understanding of disease drivers. We fit modified Time-series Susceptible-Infectious-Recovered models to city-level weekly mortality counts to estimate seasonal and long-term typhoid transmission. We examined seasonal transmission separately by city and aggregated by water source. Typhoid transmission peaked in late summer/early fall. Seasonality varied by water source, with the greatest variation occurring in cities with reservoirs. We then fit hierarchical regression models to measure associations between long-term transmission and annual financial investments in water and sewer systems. Overall historical $1 per capita ($16.13 in 2017) investments in the water supply were associated with approximately 5% (95% confidence interval: 3-6%) decreases in typhoid transmission, while $1 increases in the overall sewer system investments were associated with estimated 6% (95% confidence interval: 4-9%) decreases. Our findings aid in the understanding of typhoid transmission dynamics and potential impacts of water and sanitation improvements, and can inform cost-effectiveness analyses of interventions to reduce the typhoid burden.

Long-term trends in seasonality of mortality in urban Madagascar: the role of the epidemiological transition

ABSTRACT Background: Seasonal patterns of mortality have been identified in Sub-Saharan Africa but their changes over time are not well documented. Objective: Based on death notification data from Antananarivo, the capital city of Madagascar, this study assesses seasonal patterns of all-cause and cause-specific mortality by age groups and evaluates how these patterns changed over the period 1976–2015. Methods: Monthly numbers of deaths by cause were obtained from death registers maintained by the Municipal Hygiene Office in charge of verifying deaths before the issuance of burial permits. Generalized Additive Mixed regression models (GAMM) were used to test for seasonality in mortality and its changes over the last four decades, controlling for long-term trends in mortality. Results: Among children, risks of dying were the highest during the hot and rainy season, but seasonality in child mortality has significantly declined since the mid-1970s, as a result of declines in the burden of infectious diseases and nutritional deficiencies. In adults aged 60 and above, all-cause mortality rates are the highest in the dry and cold season, due to peaks in cardiovascular diseases, with little change over time. Overall, changes in the seasonality of all-cause mortality have been driven by shifts in the hierarchy of causes of death, while changes in the seasonality within broad categories of causes of death have been modest. Conclusion: Shifts in disease patterns brought about by the epidemiological transition, rather than changes in seasonal variation in cause-specific mortality, are the main drivers of trends in the seasonality of all-cause mortality.