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Mosquitoes of the genus transmit arboviruses of great importance to human health as dengue, chikungunya, Zika and yellow fever. The tiger mosquito can play an important role as arboviral vector, especially when is absent or present at low levels. Remarkably, the rapid worldwide spreading of the tiger mosquito is expanding the risk of arboviral transmission also to temperate areas, and the autochthonous cases of chikungunya, dengue and Zika in Europe emphasize the need for improved monitoring and control. Proteomic and transcriptomic studies on blood feeding arthropod salivary proteins paved the way toward the exploitation of genus-specific mosquito salivary proteins for the development of novel tools to evaluate human exposure to mosquito bites. We previously found that the culicine-specific 34k2 salivary protein from (al34k2) evokes specific IgG responses in experimentally exposed mice, and provided preliminary evidence of its immunogenicity to humans. In this study we measured IgG responses to al34k2 and to salivary gland protein extracts (SGE) in individuals naturally exposed to the tiger mosquito. Sera were collected in two areas of Northeast Italy (Padova and Belluno) during two different time periods: at the end of the low- and shortly after the high-density mosquito seasons. Anti-SGE and anti-al34k2 IgG levels increased after the summer period of exposure to mosquito bites and were higher in Padova as compared to Belluno. An age-dependent decrease of anti-saliva IgG responses was found especially in Padova, an area with at least 25 years history of colonization. Moreover, a weak correlation between anti-saliva IgG levels and individual perception of mosquito bites by study participants was found. Finally, determination of anti-al34k2 IgG1 and IgG4 levels indicated a large predominance of IgG1 antibodies. Overall, this study provides a convincing indication that antibody responses to al34k2 may be regarded as a reliable candidate marker to detect temporal and/or spatial variation of human exposure to ; a serological tool of this kind may prove useful both for epidemiological studies and to estimate the effectiveness of anti-vectorial measures.

Purpose Quantitative epidemiological tools are routinely used to assess adolescent diet and physical activity (PA) constructs (behaviour, knowledge, and awareness) as risk factors for non-communicable diseases. This study sought to synthesize evidence on the quantitative epidemiological tools that have been used to assess adolescent diet and PA constructs in low to middle-income countries (LMIC). Methods A systematised review was conducted using 3 databases (EbscoHost, Scopus and Web of Science). Results We identified 292 LMIC studies assessing adolescent diet and PA. Identified studies predominantly explored behavioural (90%) constructs with a paucity of studies investigating knowledge and awareness. The majority of studies used subjective (94%) and self-administered (78%) tools. Only 39% of LMIC studies used tools validated for their contexts. Conclusions The findings highlight the need for more contextual tools for assessing adolescent diet and PA in LMICs. Diet and PA measurement tools used in future research will need to incorporate measures of knowledge and awareness for a more comprehensive understanding of the epidemiology of diet and PA in adolescents. Furthermore, there is a need for more evidence on the reliability and validity of these tools for use, in both cross sectional and longitudinal studies, in LMIC contexts.

Numerous multimorbidity indexes exist, focused primarily or solely on somatic conditions. We developed mental multimorbidity indexes as epidemiological tools. Participants in the French NutriNet-Santé cohort (73.5% women; mean age = 59.5 ± 13.7 years; index development N = 20,000; index comparison N = 7,259) completed self-report questionnaires (2020-2022) regarding depressive symptoms, anxiety, eating disorders, insomnia, alcohol use disorders, cognitive difficulties, and the WHO Disability Assessment Schedule 2.0 (WHODAS 2.0). Using established cutoffs, participants were split into 2 groups for each condition. Tweedie regression analyses were performed with the 6 mental health conditions as exposures and the WHODAS 2.0 score as the outcome. Performance (C-index) and calibration of the indexes were compared with a simple count. A general and a sex-specific mental multimorbidity indexes were developed; both were significantly associated with the disability score. The new indexes had slightly better predictive performance than simple counts of mental disorders. We developed mental multimorbidity indexes as epidemiological research tools. Future prospective studies could investigate their predictive potential regarding outcomes such as medication use, healthcare utilization, and quality of life.

During the years since certification of smallpox eradication, the power of infectious disease surveillance has been greatly increased by new biotechnical and electronic technologies. These technologies have transformed the way that surveillance can be used to contribute to public health, and to infectious disease eradication and elimination. In addition to permitting precise geographical placement of infections by incorporating the most up to date geographical positioning systems, infectious disease surveillance can now also provide more comprehensive understanding of the spread and risks of infections because of genomic sequencing that leads to more meaningful epidemiological analysis. These new technologies have made infectious disease surveillance an even more powerful and timely tool than it was during the period of smallpox eradication. Future surveillance will continue to refine these technologies, and adapt newer ones such as rapid point of care diagnostics and hand held communication devices that will lead to more timely and accurate reporting from health facilities. These technologies will also lead to the possibility of direct participation in surveillance by individuals who will be able to report their own disease syndromes, those of their neighbors, or those of domestic and wild animals at the animal/human interface.

Background The standard measurement of oral conditions that are mainly of cosmetic concern can be carried out by a trained clinical professional, or they can be assessed and reported by the individuals who may have the condition or be aware of others who have it. Enamel opacities of anterior teeth are examples of such a condition. At a public health level the interest is only about opacities that are of aesthetic concern, so the need for an index that records opacities that the public perceive to be a problem is clear. Measurement methods carried out by highly trained professionals, using unnatural conditions are not indicated at this level. This study reports on the testing of a novel epidemiological tool that aims to report on the prevalence and impact of self-perceived enamel opacities in a population of young adolescents. Methods A dental health survey was carried out using a random sample of 12-year-old school pupils during 2008/09 by Primary Care Organisations (PCOs) in England. This included the use of a novel self-perception tool which aimed to measure individual’s self-perception of the presence and impact of enamel opacities to produce population measures. This tool comprised questions asking about the presence of white marks on their teeth and whether these marks bothered the volunteers and a sheet of grouped photographs of anterior teeth showing opacities ranging from TF 0, TF 1–2 to TF 2–3. Volunteers were asked which of the groups of photographs looked more like their own teeth. Examining teams from a convenience sample of 3 PCOs from this survey agreed to undertake additional measurements to assess the value of the self-perception tool. Volunteer pupils were asked the questions on a second occasion, some time after the first and clinical examiners recorded their assessments of the most closely matching set of photographs of the volunteers on two occasions. Results The tool was feasible to use, with 74% of pupils making a response to the first question about the presence of white marks on front teeth, 94% to the second (do these marks bother you?) and 79% to the third about which set of images most closely matched the volunteer’s own, with regard to white marks. Responses to these sequential questions showed coherence with pupils who perceived themselves as having white marks on their teeth being more likely to select images that showed teeth with opacities to match with their appearance. Pupils who reported themselves concerned about their white marks were the most likely to select images with the most severe opacities. Repeatability was good among pupils (Kappa = 0.65) and very good among examiners (Kappa = 0.87). Agreement levels between pupil’s and examiner’s choice of images was poor as examiners were less likely than pupils to select images that showed more severe levels of mottling. Conclusions With regard to feasibility, coherence and repeatability the standardised epidemiological tool under scrutiny, with operator training, appears to be a suitable method for measuring the prevalence and impact of self-perceived enamel opacities in a population of young adolescents.

Ecological studies lack the ability to control for the effects of confounding factors. The findings of a linear relationship between average exposure and disease frequency in ecological studies do not imply that such a linear relationship will be present at the individual levels. This is known as the ‘ecological fallacy’. Despite these limitations, ecological studies may be the best approach to studying exposures that are easier to measure at the group rather than the individual level because most ecological studies make use of routinely collected data. They are also useful for monitoring the effectiveness of population interventions such as vaccination programs, health education campaigns and mass screening programs. Thus, ecological studies are useful epidemiologic tools for public health surveillance if we know their limitations and interpret their results carefully. Ecological studies often help to generate hypotheses, although they rarely provide a strong test of a causal hypothesis.

The microbiological safety of food has always been essential to ensuring the public's well‐being; however, over the past decade, many issues have emerged or continue to be of concern. Four of these topics are addressed in this chapter. The application of whole‐genome sequencing to enhance the identification and investigation of outbreaks of foodborne illness through its use as a standard tool for “fingerprinting‐ pathogens has revolutionized surveillance of foodborne‐illness outbreaks and source tracking. Implementation of the U.S. Food and Drug Administration's recently adopted rules of the Food Safety Modernization Act is another factor that should contribute to the enhanced safety of foods, and a brief discussion of the intricacies of this law is provided, highlighting features that are likely to have the greatest impact. Although the food industry generally has a remarkable record of producing safe foods, it is increasingly challenged by consumers' demand for “natural‐ foods that are free of synthetic antimicrobials. In addition, an ever‐increasing percentage of foods consumed in the United States and in many developed countries are imported, of which a major portion originate from developing countries whose sanitary practices in production and processing are often inferior to those employed in developed countries. The food safety landscape is not likely to remain static; however, improvements will need to be balanced against competing nutritional, cost, and sustainability priorities.

Comparing the impact of the COVID-19 pandemic between countries or across time is difficult because the reported numbers of cases and deaths can be strongly affected by testing capacity and reporting policy. Excess mortality, defined as the increase in all-cause mortality relative to the expected mortality, is widely considered as a more objective indicator of the COVID-19 death toll. However, there has been no global, frequently updated repository of the all-cause mortality data across countries. To fill this gap, we have collected weekly, monthly, or quarterly all-cause mortality data from 103 countries and territories, openly available as the regularly updated World Mortality Dataset. We used this dataset to compute the excess mortality in each country during the COVID-19 pandemic. We found that in several worst-affected countries (Peru, Ecuador, Bolivia, Mexico) the excess mortality was above 50% of the expected annual mortality (Peru, Ecuador, Bolivia, Mexico) or above 400 excess deaths per 100,000 population (Peru, Bulgaria, North Macedonia, Serbia). At the same time, in several other countries (e.g. Australia and New Zealand) mortality during the pandemic was below the usual level, presumably due to social distancing measures decreasing the non-COVID infectious mortality. Furthermore, we found that while many countries have been reporting the COVID-19 deaths very accurately, some countries have been substantially underreporting their COVID-19 deaths (e.g. Nicaragua, Russia, Uzbekistan), by up to two orders of magnitude (Tajikistan). Our results highlight the importance of open and rapid all-cause mortality reporting for pandemic monitoring. Countries around the world reported 4.2 million deaths from SARS-CoV-2 (the virus that causes COVID-19) from the beginning of pandemic until the end of July 2021, but the actual number of deaths is likely higher. While some countries may have imperfect systems for counting deaths, others may have intentionally underreported them. To get a better estimate of deaths from an event such as a pandemic, scientists often compare the total number of deaths in a country during the event to the expected number of deaths based on data from previous years. This tells them how many excess deaths occurred during the event. To provide a more accurate count of deaths caused by COVID-19, Karlinsky and Kobak built a database called the World Mortality Dataset. It includes information on deaths from all causes from 103 countries. Karlinsky and Kobak used the database to compare the number of reported COVID-19 deaths reported to the excess deaths from all causes during the pandemic. Some of the hardest hit countries, including Peru, Ecuador, Bolivia, and Mexico, experienced over 50% more deaths than expected during the pandemic. Meanwhile, other countries like Australia and New Zealand, reported fewer deaths than normal. This is likely because social distancing measures reduced deaths from infections like influenza. Many countries reported their COVID-19 deaths accurately, but Karlinsky and Kobak argue that other countries, including Nicaragua, Russia, and Uzbekistan, underreported COVID-19 deaths. Using their database, Karlinsky and Kobak estimate that, in those countries, there have been at least 1.4 times more deaths due to COVID-19 than reported – adding over 1 million extra deaths in total. But they note that the actual number is likely much higher because data from more than 100 countries were not available to include in the database. The World Mortality Dataset provides a more accurate picture of the number of people who died because of the COVID-19 pandemic, and it is available online and updated daily. The database may help scientists develop better mitigation strategies for this pandemic or future ones.

Clinical guideline development preferentially relies on evidence from randomized controlled trials (RCTs). RCTs are gold-standard methods to evaluate the efficacy of treatments with the highest internal validity but limited external validity, in the sense that their findings may not always be applicable to or generalizable to clinical populations or population characteristics. The external validity of RCTs for the clinical population is constrained by the lack of tailored epidemiological data analysis designed for this purpose due to data governance, consistency of disease or condition definitions, and reduplicated effort in analysis code. This study aims to develop a digital tool that characterizes the overall population and differences between clinical trial eligible and ineligible populations from the clinical populations of a disease or condition regarding demography (eg, age, gender, ethnicity), comorbidity, coprescription, hospitalization, and mortality. Currently, the process is complex, onerous, and time-consuming, whereas a real-time tool may be used to rapidly inform a guideline developer's judgment about the applicability of evidence. The National Institute for Health and Care Excellence-particularly the gout guideline development group-and the Scottish Intercollegiate Guidelines Network guideline developers were consulted to gather their requirements and evidential data needs when developing guidelines. An R Shiny (R Foundation for Statistical Computing) tool was designed and developed using electronic primary health care data linked with hospitalization and mortality data built upon an optimized data architecture. Disclosure control mechanisms were built into the tool to ensure data confidentiality. The tool was deployed within a Trusted Research Environment, allowing only trusted preapproved researchers to conduct analysis. The tool supports 128 chronic health conditions as index conditions and 161 conditions as comorbidities (33 in addition to the 128 index conditions). It enables 2 types of analyses via the graphic interface: overall population and stratified by user-defined eligibility criteria. The analyses produce an overview of statistical tables (eg, age, gender) of the index condition population and, within the overview groupings, produce details on, for example, electronic frailty index, comorbidities, and coprescriptions. The disclosure control mechanism is integral to the tool, limiting tabular counts to meet local governance needs. An exemplary result for gout as an index condition is presented to demonstrate the tool's functionality. Guideline developers from the National Institute for Health and Care Excellence and the Scottish Intercollegiate Guidelines Network provided positive feedback on the tool. The tool is a proof-of-concept, and the user feedback has demonstrated that this is a step toward computer-interpretable guideline development. Using the digital tool can potentially improve evidence-driven guideline development through the availability of real-world data in real time.

Wastewater-based epidemiology (WBE) has contributed significantly to the monitoring of drug use and transmission of viruses that has been published in numerous research papers. In this paper, we used LitStraw, a self-developed text extraction tool, to extract, analyze, and construct knowledge graphs from nearly 900 related papers in PDF format collected in Web of Science from 2000 to 2021 to analyze the research hotspots and development trends of WBE. The results showed a growing number of WBE publications in multidisciplinary cross-collaboration, with more publications and close collaboration between the USA, Australia, China, and European countries. The keywords of illicit drugs and pharmaceuticals still maintain research hotness, but the specific research hotspots change significantly, among which the research hotspots of new psychoactive substances, biomarkers, and stability show an increasing trend. In addition, judging the spread of COVID-19 by the presence of SARS-CoV-2 RNA in sewage has become the focus since 2020. This work can show the development of WBE more clearly by constructing a knowledge graph and also provide new ideas for the paper mining analysis methods in different fields.