Whole-Genome Sequencing Reveals Recent Transmission of Multidrug-Resistant Mycobacterium tuberculosis CAS1-Kili Strains in Lusaka, Zambia

Globally, tuberculosis (TB) is a major cause of death due to antimicrobial resistance. Mycobacterium tuberculosis CAS1-Kili strains that belong to lineage 3 (Central Asian Strain, CAS) were previously implicated in the spread of multidrug-resistant (MDR)-TB in Lusaka, Zambia. Thus, we investigated recent transmission of those strains by whole-genome sequencing (WGS) with Illumina MiSeq platform. Twelve MDR CAS1-Kili isolates clustered by traditional methods (MIRU-VNTR and spoligotyping) were used. A total of 92% (11/12) of isolates belonged to a cluster (≤12 SNPs) while 50% (6/12) were involved in recent transmission events, as they differed by ≤5 SNPs. All the isolates had KatG Ser315Thr (isoniazid resistance), EmbB Met306 substitutions (ethambutol resistance) and several kinds of rpoB mutations (rifampicin resistance). WGS also revealed compensatory mutations including a novel deletion in embA regulatory region (−35A > del). Several strains shared the same combinations of drug-resistance-associated mutations indicating transmission of MDR strains. Zambian strains belonged to the same clade as Tanzanian, Malawian and European strains, although most of those were pan-drug-susceptible. Hence, complimentary use of WGS to traditional epidemiological methods provides an in-depth insight on transmission and drug resistance patterns which can guide targeted control measures to stop the spread of MDR-TB.

The Layers of Life

Chapter 6 summarizes the work described in the book. It places Environmental Biodynamics in context of the broader field of general systems theory. It argues that to realize the full potential of Environmental Biodynamics, environmental medicine must refocus the examination of the interaction of environment and health from an emphasis on measuring physiological “moments” (i.e., static measures of environmental factors, infrequent anthropometry, momentary health indicators) to studying dynamic human–environment interfaces, physiological states, and the processes that constrain to those states. To this end, Chapter 6 provides a set of endeavors that must be undertaken to capitalize on and formally test the biodynamic interface paradigm. First, focus scientific inquiry on interfaces that connect biological and environmental systems; second, develop theoretical frameworks that focus on the identification and interpretation of constraints in biological–environmental interfaces; and third, develop laboratory, clinical, and epidemiological methods to relate the complexity characterized at the level of biodynamic interfaces to human health.

The Geometry of Health

Chapter 5 examines the dynamic nature of interfaces and starts examining their characteristics. The authors posit that just as we might derive a multitude of dimensions to describe biological structure, so too are there many dimensions that describe the functional dynamics in how biological systems vary over time. Current environmental epidemiological methods used in analyzing data on our environment and our physiology treat each measure as if it were an independent dimension, much like a carpenter measuring the height, width, or length of a piece of furniture. However, because there are processes underlying our physiological development, constraints are applied to the forms that we and our environment can take. Knowledge of these can be harnessed to identify the primary dimensions along which we must characterize the systems under study. By doing this we were able to take an important first step in operationalizing Environmental Biodynamics for clinical application.

Epidemiological methods used in the periodontal health research in military personnel: a systematic review

IntroductionPeriodontal disease is a prevalent pathology in military personnel worldwide. The objective is to analyse the methodological features of periodontal health research performed in military personnel in their home countries.MethodsA PRISMA systematic review of literature was carried out in PubMed, EMBASE and Web of Science databases on military periodontal health studies. Study design type, language, publication date, year, country, size and sample selection, age, sex, military, diagnostic procedure, examiners, periodontal, gingival and oral hygiene index were extracted.ResultsEighty-eight out of 5355 studies found were selected, published between 1921 and 2020, with samples ranging from 52 to 16 869 individuals, generally not randomised, and consisting mainly of men with a mean age of 25 years. Predominant studies were cross-sectional descriptive studies, carried out in the Army, on American military personnel, and in the English language. Most of the studies used the WHO periodontal probe handled by two or more examiners. The Löe and Silness gingival index and the Silness and Löe plaque index were the most used indexes to assess gingival condition and oral hygiene, respectively. Community Periodontal Index of Treatment Needs was the most widely used periodontal index.ConclusionsResearch on periodontal health carried out in military populations from the 1920s to the present has been performed from an almost exclusively descriptive approach. Issues such as the characteristics and representativeness of the samples, the epidemiological design and the different gingival-periodontal indexes used may limit the comparability of the study results.

An outbreak of COVID-19 associated with a fitness centre in Saskatchewan: Lessons for prevention

Background: An outbreak of the coronavirus disease 2019 (COVID-19) occurred in Saskatchewan from September 12 to October 20, 2020. The index event, attendance at a local gym, seeded six additional clusters/outbreaks in multiple settings. These included a high school, a hospital, three workplaces (A, B and C) and several households. The overall cluster comprised 63 cases, 27 gym members and an additional 36 second, third and fourth generation cases. Methods: All outbreak-related, laboratory-confirmed cases of COVID-19 were included in the analysis. Local public health authorities interviewed all cases and contacts and conducted environmental investigations of the fitness facility. We used descriptive epidemiological methods to understand transmission dynamics of the gym-associated cluster using case investigation, contact investigation and laboratory data, including whole genome sequencing. Results: Sequencing data confirmed the unique lineage of cluster-related cases (n=32 sequenced; severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2] lineage B.1.1.72). In addition to gym attendance, infectious cases attended high school and were involved in other activities. Despite ongoing transmission in the fitness facility, no secondary cases were identified in the high school where four student belonging to the cluster attended class during their infectious period. Conclusion: We describe an outbreak of COVID-19 where the index case(s) attended a fitness facility, and further spread occurred for 38 days despite active-case finding and isolation of positive cases over this period. Due to gym attendance over time, short-term closing and cleaning may not interrupt chains of transmission. Targeted, preventive public health action in fitness facilities may be warranted. Control measures worked to limit in-school acquisition.

Epidemiology

Epidemiology is the basic science of public health, because it is the science that describes the relationship of health and/or disease with other health-related factors in human populations, such as human pathogens. Furthermore, epidemiology has been used to generate much of the information required by public health professionals to develop, implement, and evaluate effective intervention programmes for the prevention of disease and promotion of health. Unlike pathology, which constitutes a basic area of knowledge, and cardiology, which is the study of a specific organ, epidemiology is a philosophy and methodology that can be applied to learning about and resolving a very broad range of health problems. It is not enough to know what the various study designs and statistical methodologies are. The ‘art’ of epidemiology is knowing when and how to apply the various epidemiological strategies creatively to answer specific health questions. The uses and limitations of the various epidemiological study designs are presented in this chapter to illustrate and underscore the fact that the successful application of epidemiology requires more than knowledge of study designs and epidemiological methods. This introductory chapter attempts to define epidemiology, to present ways in which epidemiology is used in the advancement of public health, and finally, to discuss the range of applications of epidemiological methodologies.

Clinical epidemiology

Clinical epidemiology is a science that extends the principles and methods of epidemiology to clinical practice and clinical research. In this chapter, we provide an overview of clinical epidemiological methods and how these approaches can be used to improve global public health. We have focused primarily on using evidence in decision-making in this chapter, rather than study design and conduct elements, such as randomized controlled trials, which are covered in detail elsewhere. Consequently, we have provided a framework for critical appraisal and reporting of relevant study designs (how to use and report), rather than a detailed discussion about how such studies should be designed and conducted (how to do).

A Review on Epidemiological Methods to Detect Untrue Information

Online propagation of untrue information has been and is becoming an increasing problem. Understanding and modeling the diffusion of information on Online Social Networks (OSN's) of voluminous data is the prime concern. The paper provides the history of the epidemic spread and its analogy with untrue information. This paper provides a review of untrue information on online social networks and methods of detection of untrue information based on epidemiological models. Open research challenges and potential future research directions are also highlighted. The paper aimed at aiding research for the identification of untrue information on OSNs.

A Review on Epidemiological Methods to Detect Untrue Information

Online propagation of untrue information has been and is becoming an increasing problem. Understanding and modeling the diffusion of information on Online Social Networks (OSN's) of voluminous data is the prime concern. The paper provides the history of the epidemic spread and its analogy with untrue information. This paper provides a review of untrue information on online social networks and methods of detection of untrue information based on epidemiological models. Open research challenges and potential future research directions are also highlighted. The paper aimed at aiding research for the identification of untrue information on OSNs.

1363Just a flu? Comparing COVID-19 and influenza mortality

Background Benchmarks are needed for assessing the severity of the COVID-19 pandemic. However, comparisons can be misleading unless marked differences in age-specific mortality and differences in population age structure are considered. Methods Using COVID-19 death rates for New York City as at 2 June 2020, we used indirect age standardization to estimate standardized mortality ratios (SMR) for the first winter waves of the 1918 and 2009 influenza pandemics and the severe 2017-2018 influenza season in the United States (US). Data were obtained from published statistics. Results After adjusting for age, New York City’s death rate during the 1918 winter influenza pandemic wave was 6.7 times higher overall compared with the first wave of COVID-19 in 2020. New York City's first wave COVID-19 death rate was an estimated 59 times higher than that of the 2009 US influenza pandemic, and 14 times higher than that of the severe 2017-2018 influenza season. In < 45 year-olds, the 1918 influenza death rate was 42 times higher than COVID-19 in 2020. In ≥ 65 year-olds, compared with the 2009 pandemic, the COVID-19 death rate was 320 times higher, while in children it was one half. Conclusions The 1918 pandemic was more deadly than COVID-19, which was, in turn, far more deadly than both the 2009 influenza pandemic and severe seasonal influenza. Age-specific mortality differences should be considered in decisions on COVID-19 vaccination strategies. Key messages Fundamental epidemiological methods remain valuable for modern epidemic risk assessment. COVID-19 is not just a ‘flu’.