Infectious Diseases In Human Populations Research Articles

Quantifying human mixing patterns in Chinese provinces outside Hubei after the 2020 lockdown was lifted

BackgroundContact patterns play a key role in the spread of respiratory infectious diseases in human populations. During the COVID-19 pandemic, the regular contact patterns of the population have been disrupted due to social distancing both imposed by the authorities and individual choices. Many studies have focused on age-mixing patterns before the COVID-19 pandemic, but they provide very little information about the mixing patterns in the COVID-19 era. In this study, we aim at quantifying human heterogeneous mixing patterns immediately after lockdowns implemented to contain COVID-19 spread in China were lifted. We also provide an illustrative example of how the collected mixing patterns can be used in a simulation study of SARS-CoV-2 transmission.Methods and resultsIn this work, a contact survey was conducted in Chinese provinces outside Hubei in March 2020, right after lockdowns were lifted. We then leveraged the estimated mixing patterns to calibrate a mathematical model of SARS-CoV-2 transmission. Study participants reported 2.3 contacts per day (IQR: 1.0–3.0) and the mean per-contact duration was 7.0 h (IQR: 1.0–10.0). No significant differences in average contact number and contact duration were observed between provinces, the number of recorded contacts did not show a clear trend by age, and most of the recorded contacts occurred with family members (about 78%). The simulation study highlights the importance of considering age-specific contact patterns to estimate the COVID-19 burden.ConclusionsOur findings suggest that, despite lockdowns were no longer in place at the time of the survey, people were still heavily limiting their contacts as compared to the pre-pandemic situation.

Diversity in valuing social contact and risk tolerance leading to the emergence of homophily in populations facing infectious threats.

How self-organization leads to the emergence of structure in social populations remains a fascinating and open question in the study of complex systems. One frequently observed structure that emerges again and again across systems is that of self-similar community, i.e., homophily. We use a game theoretic perspective to explore a case in which individuals choose affiliation partnerships based on only two factors: the value they place on having social contacts, and their risk tolerance for exposure to threat derived from social contact (e.g., infectious disease, threatening ideas, etc.). We show how diversity along just these two influences is sufficient to cause the emergence of self-organizing homophily in the population. We further consider a case in which extrinsic social factors influence the desire to maintain particular social ties, and show the robustness of emergent homophilic patterns to these additional influences. These results demonstrate how observable population-level homophily may arise out of individual behaviors that balance the value of social contacts against the potential risks associated with those contacts. We present and discuss these results in the context of outbreaks of infectious disease in human populations. Complementing the standard narrative about how social division alters epidemiological risk, we here show how epidemiological risk may deepen social divisions in human populations.

The Incidence and Magnitude of the Health Costs of In-person Schooling during the COVID-19 Pandemic

The health costs of in-person schooling during the pandemic, if any, fall primarily on the families of students, largely due to the fact that students significantly outnumber teachers. Data from North Carolina, Wisconsin, Australia, England, and Israel covering almost 80 million person-days in school help assess the magnitude of the fatality risks of in-person schooling (with mitigation protocols), accounting for the age and living arrangements of students and teachers. The risks of in-person schooling to teachers are comparable to the risks of commuting by automobile. Valued at a VSL of $10 million, the average daily fatality cost ranges from $0.01 for an unvaccinated young teacher living alone to as much as $29 for an elderly and unvaccinated teacher living with an elderly and unvaccinated spouse. COVID-19 risk avoidance may also be more amenable to Bayesian updating and selective protection than automobile fatalities are. The results suggest that economic behaviors can sometimes invert epidemiological patterns when it comes to the spread of infectious diseases in human populations.

Epidemics Forecast From SIR-Modeling, Verification and Calculated Effects of Lockdown and Lifting of Interventions

Due to the current COVID-19 epidemic plague hitting the worldwide population it is of utmost medical, economical and societal interest to gain reliable predictions on the temporal evolution of the spreading of the infectious diseases in human populations. Of particular interest are the daily rates and cumulative number of new infections, as they are monitored in infected societies, and the influence of non-pharmaceutical interventions due to different lockdown measures as well as their subsequent lifting on these infections. Estimating quantitatively the influence of a later lifting of the interventions on the resulting increase in the case numbers is important to discriminate this increase from the onset of a second wave. The recently discovered new analytical solutions of Susceptible-Infectious-Recovered (SIR) model allow for such forecast. In particular, it is possible to test lockdown and lifting interventions because the new solutions hold for arbitrary time dependence of the infection rate. Here we present simple analytical approximations for the rate and cumulative number of new infections.

Spatio-temporal variation in environmental features predicts the distribution and abundance of Ixodes scapularis

Many species have experienced dramatic changes in both geographic range and population sizes in recent history. Increases in the geographic range or population size of disease vectors have public health relevance as these increases often precipitate the emergence of infectious diseases in human populations. Accurately identifying environmental factors affecting the biogeographic patterns of vector species is a long-standing analytical challenge, stemming from a paucity of data capturing periods of rapid changes in vector demographics. We systematically investigated the occurrence and abundance of nymphal Ixodes scapularis ticks at 532 sampling locations throughout New York State (NY), USA, between 2008 and 2018, a time frame that encompasses the emergence of diseases vectored by these ticks. Analyses of these field-collected data demonstrated a range expansion into northern and western NY during the last decade. Nymphal abundances increased in newly colonised areas, while remaining stable in areas with long-standing populations over the last decade. These trends in the geographic range and abundance of nymphs correspond to both the geographic expansion of human Lyme disease cases and increases in incidence rates. Analytic models fitted to these data incorporating time, space, and environmental factors, accurately identified drivers of the observed changes in nymphal occurrence and abundance. These models accounted for the spatial and temporal variation in the occurrence and abundance of nymphs and can accurately predict nymphal population patterns in future years. Forecasting disease risk at fine spatial scales prior to the transmission season can influence both public health mitigation strategies and individual behaviours, potentially impacting tick-borne disease risk and subsequently human disease incidence.

A review of HLA allele and SNP associations with highly prevalent infectious diseases in human populations.

Human leucocyte antigen (HLA) alleles and single nucleotide polymorphisms (SNPs) lying in the HLA region are known to be associated with several infectious diseases among which acquired immunodeficiency syndrome, hepatitis B, hepatitis C, tuberculosis, leprosy and malaria are highly prevalent in many human populations worldwide. Distinct approaches such as case-control comparisons, immunogenetic analyses, bioinformatic peptide-binding predictions, ancient DNA and genome-wide association studies (GWAS) have contributed to improving this knowledge during the last decade, although many results still need stronger statistical and/or functional support. The present review updates the information regarding the main HLA allele and SNP associations observed to date for six of the most widespread and some other infectious diseases, and provides a synthetic illustration of these findings on a schematic HLA genomic map. It then discusses these results by stressing the importance of integrating information on HLA population diversity in disease-association studies.

When to vaccinate a fluctuating wildlife population: Is timing everything?

Wildlife vaccination is an important tool for managing the burden of infectious disease in human populations, domesticated livestock and various iconic wildlife. Although substantial progress has been made in the field of vaccine designs for wildlife, there is a gap in our understanding of how to time wildlife vaccination, relative to host demography, to best protect a population.We use a mathematical model and computer simulations to assess the outcomes of vaccination campaigns that deploy vaccines once per annual population cycle.Optimal timing of vaccination is an important consideration in animals with short to intermediate life spans and a short birthing season. Vaccines that are deployed shortly after the birthing season best protect the host population.The importance of timing is greater in wildlife pathogens that have a high rate of transmission and a short recovery period. Vaccinating at the end of the birthing season best reduces the mean abundance of pathogen‐infected hosts. Delaying vaccination until later in the year can facilitate pathogen elimination. Policy Implications. Tuning wildlife vaccination campaigns to host demography and pathogen traits can substantially increase the effectiveness of a campaign. Our results suggest that, for a fluctuating population, vaccinating at, or shortly after, the end of the birthing season, best protects the population against an invading pathogen. If the pathogen is already endemic, delaying vaccination until after the birthing season is over can help facilitate pathogen elimination. Our results highlight the need to better understand and predict host demography in wildlife populations that are targeted for vaccination.

Phage-Resistant Phase-Variant Sub-populations Mediate Herd Immunity Against Bacteriophage Invasion of Bacterial Meta-Populations.

Hypermutable loci are widespread in bacteria as mechanisms for rapid generation of phenotypic diversity within a population that enables survival of fluctuating, often antagonistic, selection pressures. Localized hypermutation can mediate phase variation and enable survival of bacteriophage predation due to high frequency, reversible alterations in the expression of phage receptors. As phase variation can also generate population-to-population heterogeneity, we hypothesized that this phenomenon may facilitate survival of spatially-separated bacterial populations from phage invasion in a manner analogous to herd immunity to infectious diseases in human populations. The lic2A gene of Haemophilus influenzae is subject to “ON” and “OFF” switches in expression mediated by mutations in a 5′CAAT repeat tract present within the reading frame. The enzyme encoded by lic2A mediates addition of a galactose moiety of the lipopolysaccharide. This moiety is required for attachment of the HP1C1 phage such that the ON state of the lic2A gene is associated with HP1c1 susceptibility while the OFF state is resistant to infection. We developed an “oscillating prey assay” to examine phage spread through a series of sub-populations of Haemophilus influenzae whose phage receptor is in an ON or OFF state. Phage extinction was frequently observed when the proportion of phage-resistant sub-populations exceeded 34%. In silico modeling indicated that phage extinction was interdependent on phage loss during transfer between sub-populations and the frequency of resistant sub-populations. In a fixed-area oscillating prey assay, heterogeneity in phage resistance was observed to generate vast differences in phage densities across a meta-population of multiple bacterial sub-populations resulting in protective quarantining of some sub-populations from phage attack. We conclude that phase-variable hypermutable loci produce bacterial “herd immunity” with resistant intermediary-populations acting as a barricade to reduce the viral load faced by phage-susceptible sub-populations. This paradigm of meta-population protection is applicable to evolution of hypermutable loci in multiple bacteria-phage and host-pathogen interactions.

Evidence for a recombinant origin of HIV-1 Group M from genomic variation.

Reconstructing the early dynamics of the HIV-1 pandemic can provide crucial insights into the socioeconomic drivers of emerging infectious diseases in human populations, including the roles of urbanization and transportation networks. Current evidence indicates that the global pandemic comprising almost entirely of HIV-1/M originated around the 1920s in central Africa. However, these estimates are based on molecular clock estimates that are assumed to apply uniformly across the virus genome. There is growing evidence that recombination has played a significant role in the early history of the HIV-1 pandemic, such that different regions of the HIV-1 genome have different evolutionary histories. In this study, we have conducted a dated-tip analysis of all near full-length HIV-1/M genome sequences that were published in the GenBank database. We used a sliding window approach similar to the ‘bootscanning’ method for detecting breakpoints in inter-subtype recombinant sequences. We found evidence of substantial variation in estimated root dates among windows, with an estimated mean time to the most recent common ancestor of 1922. Estimates were significantly autocorrelated, which was more consistent with an early recombination event than with stochastic error variation in phylogenetic reconstruction and dating analyses. A piecewise regression analysis supported the existence of at least one recombination breakpoint in the HIV-1/M genome with interval-specific means around 1929 and 1913, respectively. This analysis demonstrates that a sliding window approach can accommodate early recombination events outside the established nomenclature of HIV-1/M subtypes, although it is difficult to incorporate the earliest available samples due to their limited genome coverage.

Using cultural, historical, and epidemiological data to inform, calibrate, and verify model structures in agent-based simulations.

Agent-based simulation models are excellent tools for addressing questions about the spread of infectious diseases in human populations because realistic, complex behaviors as well as random factors can readily be incorporated. Agent-based models are flexible and allow for a wide variety of behaviors, time-related variables, and geographies, making the calibration process an extremely important step in model development. Such calibration procedures, including verification and validation, may be complicated, however, and usually require incorporation of substantial empirical data and theoretical knowledge of the populations and processes under study. This paper describes steps taken to build and calibrate an agent-based model of epidemic spread in an early 20th century fishing village in Newfoundland and Labrador, including a description of some of the detailed ethnographic and historical data available. We illustrate how these data were used to develop the structure of specific parts of the model. The resulting model, however, is designed to reflect a generic small community during the early 20th century and the spread of a directly transmitted disease within such a community, not the specific place that provided the data. Following the description of model development, we present the results of a replication study used to confirm the model behaves as intended. This study is also used to identify the number of simulations necessary for high confidence in average model output. We also present selected results from extensive sensitivity analyses to assess the effect that variation in parameter values has on model outcomes. After careful calibration and verification, the model can be used to address specific practical questions of interest. We provide an illustrative example of this process.

Potential Animal Reservoir of Mycobacterium ulcerans: A Systematic Review.

Mycobacterium ulcerans is the causative agent of Buruli ulcer, also known in Australia as Daintree ulcer or Bairnsdale ulcer. This destructive skin disease is characterized by extensive and painless necrosis of the skin and soft tissue with the formation of large ulcers, commonly on the leg or arm. To date, 33 countries with tropical, subtropical and temperate climates in Africa, the Americas, Asia and the Western Pacific have reported cases of Buruli ulcer. The disease is rarely fatal, although it may lead to permanent disability and/or disfigurement if not treated appropriately or in time. It is the third most common mycobacterial infection in the world after tuberculosis and leprosy. The precise mode of transmission of M. ulcerans is yet to be elucidated. Nevertheless, it is possible that the mode of transmission varies with different geographical areas and epidemiological settings. The knowledge about the possible routes of transmission and potential animal reservoirs of M. ulcerans is poorly understood and still remains patchy. Infectious diseases arise from the interaction of agent, host and environment. The majority of emerging or remerging infectious disease in human populations is spread by animals: either wildlife, livestock or pets. Animals may act as hosts or reservoirs and subsequently spread the organism to the environment or directly to the human population. The reservoirs may or may not be the direct source of infection for the hosts; however, they play a major role in maintenance of the organism in the environment, and in the mode of transmission. This remains valid for M. ulcerans. Possums have been suggested as one of the reservoir of M. ulcerans in south-eastern Australia, where possums ingest M. ulcerans from the environment, amplify them and shed the organism through their faeces. We conducted a systematic review with selected key words on PubMed and INFORMIT databases to aggregate available published data on animal reservoirs of M. ulcerans around the world. After certain inclusion and exclusion criteria were implemented, a total of 17 studies was included in the review. A variety of animals around the world e.g., rodents, shrews, possums (ringtail and brushtail), horses, dogs, alpacas, koalas and Indian flap-shelled turtles have been recorded as being infected with M. ulcerans. The majority of studies included in this review identified animal reservoirs as predisposing to the emergence and reemergence of M. ulcerans infection. Taken together, from the selected studies in this systematic review, it is clear that exotic wildlife and native mammals play a significant role as reservoirs for M. ulcerans.

Network Analysis of MERS Coronavirus within Households, Communities, and Hospitals to Identify Most Centralized and Super-Spreading in the Arabian Peninsula, 2012 to 2016.

Contact history is crucial during an infectious disease outbreak and vital when seeking to understand and predict the spread of infectious diseases in human populations. The transmission connectivity networks of people infected with highly contagious Middle East respiratory syndrome coronavirus (MERS-CoV) in Saudi Arabia were assessed to identify super-spreading events among the infected patients between 2012 and 2016. Of the 1379 MERS cases recorded during the study period, 321 (23.3%) cases were linked to hospital infection, out of which 203 (14.7%) cases occurred among healthcare workers. There were 1113 isolated cases while the number of recorded contacts per MERS patient is between 1 (n=210) and 17 (n=1), with a mean of 0.27 (SD = 0.76). Five super-important nodes were identified based on their high number of connected contacts worthy of prioritization (at least degree of 5). The number of secondary cases in each SSE varies (range, 5–17). The eigenvector centrality was significantly (p < 0.05) associated with place of exposure, with hospitals having on average significantly higher eigenvector centrality than other places of exposure. Results suggested that being a healthcare worker has a higher eigenvector centrality score on average than being nonhealthcare workers. Pathogenic droplets are easily transmitted within a confined area of hospitals; therefore, control measures should be put in place to curtail the number of hospital visitors and movements of nonessential staff within the healthcare facility with MERS cases.

Development of HTLV-1 associated myelopathy/tropical spastic paraparesis in a patient with simian T-lymphotropic virus type 1-like infection.

Virus transmission from various wild and domestic animals contributes to increased risk of emerging infectious diseases in human populations. HTLV-1 is a human retrovirus associated with acute T-cell leukemia (ATL) and HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP), which originated from zoonotic transmission from various African and Asian nonhuman primates (NHPs). Similar to HTLV-1, the simian counterpart, STLV-1, causes chronic infection and leukemia and lymphoma in naturally infected monkeys. However, other clinical syndromes typically seen in human such as a chronic progressive myelopathy have not been observed in NHPs. Little is also known about the development of any neurologic and inflammatory diseases in human populations infected with STLV-1-like viruses following NHP exposure. We identified and analyzed the complete genome of a primate T lymphotropic virus type 1 (PTLV-1) isolated from a patient with typical HAM/TSP who resides in the United States but was born in Liberia. Using a novel droplet digital PCR for the detection of the HTLV-1 tax gene, the proviral load in PBMC was 14.01%; however there was a distinct difference in fluorescence amplitude compared to all other H!M/TSP patient's, suggesting viral heterogeneity. A complete PTLV-1 proviral genome was amplified from DNA extracted from the PBMCs of the HAM/TSP patient using PCR to generate nine overlapping subgenomic fragments. Phylogenetic analysis of PTLV-1 env and LTR regions showed the virus was highly related with PTLV-1 from sooty mangabey monkeys and humans exposed from NHPs in West Africa. These results suggest the patient is likely infected with STLV-1, suggesting for the first time that viral transmission from monkey to human may be associated with a chronic progressive neurologic disease.

Some considerations concerning the challenge of incorporating social variables into epidemiological models of infectious disease transmission

Incorporation of ‘social’ variables into epidemiological models remains a challenge. Too much detail and models cease to be useful; too little and the very notion of infection – a highly social process in human populations – may be considered with little reference to the social. The French sociologist Émile Durkheim proposed that the scientific study of society required identification and study of ‘social currents’. Such ‘currents’ are what we might today describe as ‘emergent properties’, specifiable variables appertaining to individuals and groups, which represent the perspectives of social actors as they experience the environment in which they live their lives. Here we review the ways in which one particular emergent property, hope, relevant to a range of epidemiological situations, might be used in epidemiological modelling of infectious diseases in human populations. We also indicate how such an approach might be extended to include a range of other potential emergent properties to represent complex social and economic processes bearing on infectious disease transmission.

Nine challenges in incorporating the dynamics of behaviour in infectious diseases models

Traditionally, the spread of infectious diseases in human populations has been modelled with static parameters. These parameters, however, can change when individuals change their behaviour. If these changes are themselves influenced by the disease dynamics, there is scope for mechanistic models of behaviour to improve our understanding of this interaction. Here, we present challenges in modelling changes in behaviour relating to disease dynamics, specifically: how to incorporate behavioural changes in models of infectious disease dynamics, how to inform measurement of relevant behaviour to parameterise such models, and how to determine the impact of behavioural changes on observed disease dynamics.

The genetics of human migrations

When our human ancestors began to migrate from the African savannahs across the Alps into Northern Europe and Asia between 200,000 and 60,000 years ago, they encountered a colder climate, different food sources and new predators. Inevitably, evolution began to work on those wandering tribes: their skin became lighter, their metabolism adapted to new food sources, and their immune system had to handle different pathogens. Modern Homo sapiens began to evolve into slightly different subspecies or, as they are referred to in the common vernacular, different races. This shallow notion of race—that differences in our appearance have deep‐seated consequences for who and what we are as human beings—is the root of racism, which has led to slavery, discrimination, murder and genocide throughout the millennia. With the emergence of modern genetics and genomics, scientists had hoped that a better understanding of genetic differences and similarities among humans would eventually help to overcome the controversial and toxic notion of race as having anything to do with a person's ability, intelligence or humanity. As J. Craig Venter, then head of the Celera Genomics Corporation in Rockville, MD, USA, put it in 2000, when the first draft of the human genome was published: “Race is a social concept, not a scientific one”. Since the publication of the human genome, further advances in genomic sequencing and statistical analysis are now yielding new insights into the link between past human migrations and today's variety of genetic differences that govern disease resistance, skin pigmentation, tolerance to cold, and ability to digest or metabolize various nutrients. Such findings are contributing to discussions around the delicate issues of race, ethnicity and identity, but they are also having a significant impact on biomedical research and personalized health care. Furthermore, genetic analysis is shedding light on the migrations themselves, along with …

Natural selection and infectious disease in human populations.

The ancient biological 'arms race' between microbial pathogens and humans has shaped genetic variation in modern populations, and this has important implications for the growing field of medical genomics. As humans migrated throughout the world, populations encountered distinct pathogens, and natural selection increased the prevalence of alleles that are advantageous in the new ecosystems in both host and pathogens. This ancient history now influences human infectious disease susceptibility and microbiome homeostasis, and contributes to common diseases that show geographical disparities, such as autoimmune and metabolic disorders. Using new high-throughput technologies, analytical methods and expanding public data resources, the investigation of natural selection is leading to new insights into the function and dysfunction of human biology.

Geographical and environmental factors driving the increase in the Lyme disease vector Ixodes scapularis.

The population densities of many organisms have changed dramatically in recent history. Increases in the population density of medically relevant organisms are of particular importance to public health as they are often correlated with the emergence of infectious diseases in human populations. Our aim is to delineate increases in density of a common disease vector in North America, the blacklegged tick, and to identify the environmental factors correlated with these population dynamics. Empirical data that capture the growth of a population are often necessary to identify environmental factors associated with these dynamics. We analyzed temporally- and spatially-structured field collected data in a geographical information systems framework to describe the population growth of blacklegged ticks (Ixodes scapularis) and to identify environmental and climatic factors correlated with these dynamics. The density of the ticks increased throughout the study's temporal and spatial ranges. Tick density increases were positively correlated with mild temperatures, low precipitation, low forest cover, and high urbanization. Importantly, models that accounted for these environmental factors accurately forecast future tick densities across the region. Tick density increased annually along the south-to-north gradient. These trends parallel the increases in human incidences of diseases commonly vectored by I. scapularis. For example, I. scapularis densities are correlated with human Lyme disease incidence, albeit in a non-linear manner that disappears at low tick densities, potentially indicating that a threshold tick density is needed to support epidemiologically-relevant levels of the Lyme disease bacterium. Our results demonstrate a connection between the biogeography of this species and public health.

Network models: an underutilized tool in wildlife epidemiology?

Although the approach of contact network epidemiology has been increasing in popularity for studying transmission of infectious diseases in human populations, it has generally been an underutilized approach for investigating disease outbreaks in wildlife populations. In this paper we explore the differences between the type of data that can be collected on human and wildlife populations, provide an update on recent advances that have been made in wildlife epidemiology by using a network approach, and discuss why networks might have been underutilized and why networks could and should be used more in the future. We conclude with ideas for future directions and a call for field biologists and network modelers to engage in more cross-disciplinary collaboration.

Pestilential Complexities: Understanding Medieval Plague (review)

Reviewed by: Pestilential Complexities: Understanding Medieval Plague Jon Arrizabalaga Vivian Nutton , ed. Pestilential Complexities: Understanding Medieval Plague. Supplement no. 27 to Medical History. London: Wellcome Trust Centre for the History of Medicine, 2008. viii + 130 pp. Ill. $72.00, £35.00, €52.00 (ISBN-10: 0-85484-116-4, ISBN-13: 978-0-85484-116-5). This collective volume is focused on the endless debate about the disease identity of historical plagues, specifically that of the medieval Black Death and of subsequent epidemics that ravaged western Europe until well into the eighteenth century. Yet its aim is not so much uncovering this identity as clarifying the crucial questions that separate those who defend a common identity between historical pestilences and the bubonic plague (on the basis that their common pathogen is Yersinia pestis) from those who deny it. Pestilential Complexities includes six essays. Five are revised versions of papers presented at a 2006 conference on the matter held at the Wellcome Trust Centre for the History of Medicine at University College London by two historians with a long and fruitful research dedication to medieval plague (Ann G. Carmichael and Samuel K. Cohn, Jr.), one archaeologist of plague (Daniel Antoine), one biomedical expert on Yersinia and bubonic plague (Elisabeth Carniel), and one physiologist concerned about historical demography (Lars Walløe). The sixth essay is a brief comment by the historian Kay Peter Jankrift. An introduction by the organizer of the conference and the editor of the supplement, Vivian Nutton, provides the reader with a valuable, synthetic state of the art. The volume's contributors hold different views about the medical identity of the Black Death, and Nutton generically introduces them as "sceptics" or "believers"—as though the theory that this condition was caused by Yersinia pestis and spread primarily by rat fleas (p. 14) were a matter of faith. But the volume represents a useful interdisciplinary exercise, bringing together and discussing the evidence supplied by conceptualizations and methodologies from research areas as disparate as history, archaeology, biomedicine, and epidemiology. The volume's contents fuel the impression that the question of the medical identity of the Black Death cannot be tackled in unproblematic, reductionist terms. It might be useful to remember that the factors shaping the clinical and epidemiological peculiarities of infectious diseases in human populations are numerous, complex, and dynamic, since infectious conditions are the evolutionary expressions of parasitic interactions among living beings within specific natural and social environments subject to innumerable changes (climate, natural disasters, human action, and so on). For diseases like the bubonic plague—a primary bacterial infection of rodents, both wild and domestic, that is most often accidentally transferred to human beings through fleas that have fed on rodents' infected blood—the multiple combinations among all of these variable factors make it [End Page 778] hard not to be openly skeptical about the feasibility of retrospective diagnoses in modern medical terms. Because of the excessive expectations that historians of science and archaeologists have put on biomolecular technologies, Antoine's remarks about the reliability of molecular genetics methods, such as polymerase chain reaction in analyzing the DNA preserved within the bones and teeth of skeletal remains, and his assessment of some alleged results with regard to Yersinia pestis appear to me particularly revealing (pp. 110–13). The last sentence of Carniel's closing essay might summarize the major conclusion of the volume, namely, "Although we cannot prove anything one way or the other, it should be emphasized that it is not possible to reject the plague etiology of the Black Death simply because certain symptoms and epidemiological features do not match those found today" (p. 122). Right at the end of his introduction, Nutton claims that "the gap between sceptics and believers . . . is smaller than might be assumed at first reading," although he finds it "uncertain" that "a totally satisfactory solution can be reached" (p. 16). Not least, I may add as a skeptic on this thorny matter, because retrospectively diagnosing the historical pestilences in modern medical terms involves not only the above-mentioned biomedical difficulties, but also historiographical and epistemological ones beyond the specific question of whether the Black Death can be identified with bubonic plague. For...