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The 1918-19 influenza epidemic killed more than fifty million people worldwide. The SARS epidemic of 2002-3, by comparison, killed fewer than a thousand. The success in containing the spread of SARS was due largely to the rapid global response of public health authorities, which was aided by insights resulting from mathematical models. Models enabled authorities to better understand how the disease spread and to assess the relative effectiveness of different control strategies. In this book, Lisa Sattenspiel and Alun Lloyd provide a comprehensive introduction to mathematical models in epidemiology and show how they can be used to predict and control the geographic spread of major infectious diseases. Key concepts in infectious disease modeling are explained, readers are guided from simple mathematical models to more complex ones, and the strengths and weaknesses of these models are explored. The book highlights the breadth of techniques available to modelers today, such as population-based and individual-based models, and covers specific applications as well. Sattenspiel and Lloyd examine the powerful mathematical models that health authorities have developed to understand the spatial distribution and geographic spread of influenza, measles, foot-and-mouth disease, and SARS. Analytic methods geographers use to study human infectious diseases and the dynamics of epidemics are also discussed. A must-read for students, researchers, and practitioners, no other book provides such an accessible introduction to this exciting and fast-evolving field.

\"As doctors and biologists have learned, to their dismay, infectious disease is a moving target: new diseases emerge every year, old diseases evolve into new forms, and ecological and socioeconomic upheavals change the transmission pathways by which disease spread. By taking an approach focused on the general evolutionary and ecological dynamics of disease, this Very Short Introduction provides a general conceptual framework for thinking about disease. Ecology and evolution provide the keys to answering the 'where', 'why', 'how', and 'what' questions about any particular infectious disease: where did it come from? How is it transmitted from one person to another, and why are some individuals more susceptible than others? What biochemical, ecological, and evolutionary strategies can be used to combat the disease? Is it more effective to block transmission at the population level, or to block infection at the individual level? Through a series of case studies, Benjamin Bolker and Marta L. Wayne introduce the major ideas of infectious disease in a clear and thoughtful way, emphasising the general principles of infection, the management of outbreaks, and the evolutionary and ecological approaches that are now central to much research about infectious disease.\"--Publisher's Web site.

Trials done in infants with low birthweight in west Africa suggest that BCG vaccination reduces all-cause mortality in the neonatal period, probably because of heterologous protection against non-tuberculous infections. This study investigated whether BCG alters all-cause infectious disease morbidity in healthy infants in a different high-mortality setting, and explored whether the changes are mediated via trained innate immunity. This was an investigator-blind, randomised, controlled trial done at one hospital in Entebbe, Uganda. Infants who were born unwell (ie, those who were not well enough to be discharged directly home from the labour ward because they required medical intervention), with major congenital malformations, to mothers with HIV, into families with known or suspected tuberculosis, or for whom cord blood samples could not be taken, were excluded from the study. Any other infant well enough to be discharged directly from the labour ward was eligible for inclusion, with no limitation on gestational age or birthweight. Participants were recruited at birth and randomly assigned (1:1) to receive standard dose BCG 1331 (BCG-Danish) on the day of birth or at age 6 weeks (computer-generated randomisation, block sizes of 24, stratified by sex). Investigators and clinicians were masked to group assignment; parents were not masked. Participants were clinically followed up to age 10 weeks and contributed blood samples to one of three immunological substudies. The primary clinical outcome was physician-diagnosed non-tuberculous infectious disease incidence. Primary immunological outcomes were histone trimethylation at the promoter region of TNF, IL6, and IL1B; ex-vivo production of TNF, IL-6, IL-1β, IL-10, and IFNγ after heterologous stimulation; and transferrin saturation and hepcidin levels. All outcomes were analysed in the modified intention-to-treat population of all randomly assigned participants except those whose for whom consent was withdrawn. This trial is registered with the International Standard Randomised Controlled Trial Number registry (#59683017). Between Sept 25, 2014, and July 31, 2015, 560 participants were enrolled and randomly assigned to receive BCG at birth (n=280) or age 6 weeks (n=280). 12 participants assigned to receive BCG at birth and 11 participants assigned to receive BCG at age 6 weeks were withdrawn from the study by their parents shortly after randomisation and were not included in analyses. During the first 6 weeks of life before the infants in the delayed vaccination group received BCG vaccination, physician-diagnosed non-tuberculous infectious disease incidence was lower in infants in the BCG at birth group than in the delayed group (98 presentations in the BCG at birth group vs 129 in the delayed BCG group; hazard ratio [HR] 0·71 [95% CI 0·53–0·95], p=0·023). After BCG in the delayed group (ie, during the age 6–10 weeks follow-up), there was no significant difference in non-tuberculous infectious disease incidence between the groups (88 presentations vs 76 presentations; HR 1·10 [0·87–1·40], p=0·62). BCG at birth inhibited the increase in histone trimethylation at the TNF promoter in peripheral blood mononuclear cells occurring in the first 6 weeks of life. H3K4me3 geometric mean fold-increases were 3·1 times lower at the TNF promoter (p=0·018), 2·5 times lower at the IL6 promoter (p=0·20), and 3·1 times lower at the IL1B promoter (p=0·082) and H3K9me3 geometric mean fold-increases were 8·9 times lower at the TNF promoter (p=0·0046), 1·2 times lower at the IL6 promoter (p=0·75), and 4·6 times lower at the IL1B promoter (p=0·068), in BCG-vaccinated (BCG at birth group) versus BCG-naive (delayed BCG group) infants. No clear effect of BCG on ex-vivo production of TNF, IL-6, IL-1β, IL-10, and IFNγ after heterologous stimulation, or transferrin saturation and hepcidin concentration, was detected (geometric mean ratios between 0·68 and 1·68; p≥0·038 for all comparisons). BCG vaccination protects against non-tuberculous infectious disease during the neonatal period, in addition to having tuberculosis-specific effects. Prioritisation of BCG on the first day of life in high-mortality settings might have significant public-health benefits through reductions in all-cause infectious morbidity and mortality. Wellcome Trust. For the Luganda and Swahili translations of the abstract see Supplementary Materials section.

The spread of infectious diseases can be unpredictable. With the emergence of antibiotic resistance and worrying new viruses, and with ambitious plans for global eradication of polio and the elimination of malaria, the stakes have never been higher. Anticipation and measurement of the multiple factors involved in infectious disease can be greatly assisted by mathematical methods. In particular, modeling techniques can help to compensate for imperfect knowledge, gathered from large populations and under difficult prevailing circumstances. Heesterbeek et al. review the development of mathematical models used in epidemiology and how these can be harnessed to develop successful control strategies and inform public health policy. Science , this issue 10.1126/science.aaa4339 Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational, and spatial scales, which span hours to months, cells to ecosystems, and local to global spread. Moreover, some pathogens are directly transmitted between individuals of a single species, whereas others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity and changeable human behavior, elevate prevention and control from matters of national policy to international challenge. In the face of this complexity, mathematical models offer valuable tools for synthesizing information to understand epidemiological patterns, and for developing quantitative evidence for decision-making in global health.

Biodiversity is good for you Changes in biodiversity have the potential to either increase or reduce the incidence of infectious disease in plants and animals — including humans — because they involve interactions among species. At a minimum, this requires a host and a pathogen; often many more species are involved, including additional hosts, vectors and other organisms with which these species interact. Felicia Keesing and colleagues review the evidence that reduced biodiversity affects the transmission of infectious diseases of humans, other animals and plants. Despite important questions still to be answered, they conclude that the evidence that biodiversity exerts a protective effect on infectious diseases is sufficiently strong to include biodiversity protection as a strategy to improve health. Current unprecedented declines in biodiversity reduce the ability of ecological communities to provide many fundamental ecosystem services. Here we evaluate evidence that reduced biodiversity affects the transmission of infectious diseases of humans, other animals and plants. In principle, loss of biodiversity could either increase or decrease disease transmission. However, mounting evidence indicates that biodiversity loss frequently increases disease transmission. In contrast, areas of naturally high biodiversity may serve as a source pool for new pathogens. Overall, despite many remaining questions, current evidence indicates that preserving intact ecosystems and their endemic biodiversity should generally reduce the prevalence of infectious diseases.

Based on notification data the impact of the COVID-19 lockdown in Switzerland was assessed. While the incidence of tick-borne encephalitis almost doubled as compared to 2016-2019, a reduction in all other infectious diseases was recorded. The lowest reduction rates (<25%) were noted for legionellosis, hepatitis A, chlamydia infection and gonorrhoea.