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Tropical Medicine and Infectious Disease Disease Ecology of Rickettsial Species: A Data Science Approach

Tropical Medicine and Infectious Disease Disease Ecology of Rickettsial Species: A Data Science Approach

Second, we investigated the diversity of rickettsial species using a second database, the Enhanced Infectious Disease Database (EID2) [ 20 ] ( https://eid2.liverpool.ac.uk ). The purpose was to use a network analysis approach, which has already been shown to be of interest in representing and quantifying transmission ecology of pathogens among different individuals or different host species [ 21 ]. Network architectures of pathogens and their carriers, along with associated indices, were used here to investigate rickettsial species, their vectors and reservoirs and their transmission to humans. Modularity in bipartite and unipartite networks of pathogens in vectors and in reservoirs, respectively, that share common pathogen species may help to assess the potential risks of pathogen transmission to humans [ 22 , 23 ], and network centrality indices can provide useful information on the relative importance of a given element in a network to the structure of the whole system [ 23 ]. A given carrier (reservoir or vector) occupying a highly central position (i.e., high centrality value) in a given network may behave like a hub or a connector by linking different carriers clustered into subgroups within the network. Finally, identifying carriers with high values of centrality in networks may help in targeting key vectors or reservoirs for rickettsial disease surveillance [ 23 ].
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A systemic approach to assess the potential and risks of wildlife culling for infectious disease control

A systemic approach to assess the potential and risks of wildlife culling for infectious disease control

species), the public response to culling-based control options can facilitate or hinder their implementation. Consequently, the cost- effectiveness and cost-benefit balances of some wildlife culling options is now a topic of intense debate among scientists, policy makers, stakeholders, and the general public (Table 1 ). In this review, we assess the evidence regarding wildlife culling as a potential control strategy in several epidemiological contexts, compared with other available control options (see Supplemen- tary Fig. 1, Table 1 and the Supplementary Information for article selections from 1992 to 2018). We describe socio-ecosystem and infectious disease dynamic features that must be understood in order to design effective culling policies. Particularly, we review the range of potential consequences of culling, including its counterproductive effects on the disease system. Finally, we dis- cuss wildlife culling relative to alternative disease control policy options.
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Modern approach to infectious disease management using infrared thermal camera scanning for fever in healthcare settings.

Modern approach to infectious disease management using infrared thermal camera scanning for fever in healthcare settings.

References 1. Sun Guanghao, Akanuma Masahiko, Matsui Takemi. Clinical evaluation of the newly developed infectious disease/fever screening radar system using the neural network and fuzzy grouping method for travellers with suspected infectious dis- eases at Narita International Airport Clinic. J Infect 2016; 72(1):121 e3. http://dx.doi.org/10.1016/j.jinf.2015.09.017 . 2. Sun Guanghao, Matsui Takemi, Hakozaki Yukiya, Abe Shigeto.

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Editorial: The Mononuclear Phagocyte System in Infectious Disease

Editorial: The Mononuclear Phagocyte System in Infectious Disease

Editorial on the Research Topic The Mononuclear Phagocyte System in Infectious Disease The term “Mononuclear Phagocyte System” (MPS) was introduced by van Furth and Cohn in 1968 to describe a group of leukocytes that shared phenotypic features (e.g., a single nucleus) and biological functions (e.g., phagocytosis) ( 1 ). This term served originally to characterize bone marrow progenitors, blood monocytes, and tissue macrophages, under the assumption that it was a linear progression from progenitor to monocyte, and from monocyte to macrophage. Upon the discovery of dendritic cells (DC) in 1973 by the late Nobel Laureate, Ralph Steinman, and subsequent inclusion of this cell type as part of MPS in the late 1970s, the term “MPS” undertook a specialized function for processing and presenting antigen to activate lymphocytes ( 2 ). Monocytes, DCs, and macrophages became referred to as antigen-presenting cells (APC). Today, beyond serving as primordial APCs, these cells are also known to play roles in thermogenesis, tissue development, and organ function, maintenance of homeostasis, microbiota interactions, innate immunity against pathogens, inflammation and its resolution, and wound healing and tissue repair, among others ( 3 ). Also, it is now clear that monocytes, DCs and macrophages, are not homogenous populations ( 4 ). Recent conceptual advances concerning the MPS ontogeny and development have shattered the traditional view of DCs and macrophages as linear derivates and functional variations of monocytes ( 5 ). It is predicted that the incorporation of new technologies (e.g., mass cytometry, single-cell RNA sequencing) along with the progress in imaging capacities, will continue to unveil cellular heterogeneity and behavior in different tissues, differentiation trajectories, and the identification of novel immune functions, within the mouse and human MPS ( 5 ). Therefore, as the MPS field continues its unrelenting progress, it is important to regularly revisit the MPS conceptual framework in health and disease.
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Mathematical models for predicting human mobility in the context of infectious disease spread: introducing the impedance model

Mathematical models for predicting human mobility in the context of infectious disease spread: introducing the impedance model

Kankoé Sallah 1,2* , Roch Giorgi 1,3 , Linus Bengtsson 4,5 , Xin Lu 4,5,6 , Erik Wetter 5,7 , Paul Adrien 8 , Stanislas Rebaudet 9 , Renaud Piarroux 10 and Jean Gaudart 1,3 Abstract Background: Mathematical models of human mobility have demonstrated a great potential for infectious disease epidemiology in contexts of data scarcity. While the commonly used gravity model involves parameter tuning and is thus difficult to implement without reference data, the more recent radiation model based on population densi- ties is parameter-free, but biased. In this study we introduce the new impedance model, by analogy with electricity. Previous research has compared models on the basis of a few specific available spatial patterns. In this study, we use a systematic simulation-based approach to assess the performances.
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Review of Infectious Disease Ecology: Effects of Ecosystems on Disease and of Disease on Ecosystems by Richard S. Ostfeld, Felicia Keesing, and Valerie T. Eviner

Review of Infectious Disease Ecology: Effects of Ecosystems on Disease and of Disease on Ecosystems by Richard S. Ostfeld, Felicia Keesing, and Valerie T. Eviner

and Valerie T. Eviner Jean-François Guégan 1,2 Address: 1 Genetics and Evolution of Infectious Diseases, IRD, Montpellier, France and 2 French Center on Globalization and Infectious Diseases, French School of Public Health, Montpellier, France Email: Jean-François Guégan - guegan@mpl.ird.fr

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Requesting physician's Experiences regarding infectious disease consultation

Requesting physician's Experiences regarding infectious disease consultation

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View of Diagnosis in infectious disease

View of Diagnosis in infectious disease

Conclusion : L’apport de l’antigénurie de pneumocoque dans le bilan microbiologique initial chez les patients admis en réanimation pour une pneumonie aiguë communautaire apparaît faibl[r]

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Cost-Effective Control of Infectious Disease Outbreaks Accounting for Societal Reaction

Cost-Effective Control of Infectious Disease Outbreaks Accounting for Societal Reaction

Social responses are societal reactions to disease outbreaks. They range from anxiety to riots, violence, or flight [ 6 – 10 ]. Economic effects are also frequently observed, including the collapse of the tourism industry [ 11 ], an important source of income for many countries. The economic impact of social responses can sometimes be substantial, far outpacing the costs of the disease itself. For example, the World Bank has estimated that fear-driven changes in behavior, especially reductions in workplace productivity, travel, and consumer spending, are responsible for the bulk of the economic impact of the Ebola epidemic in West Africa [ 12 ]. Similar observations have been made about the SARS epidemic lasting from 2002 to 2004 [ 11 ]. With only 8096 cases reported worldwide [ 13 ], the direct costs of treatment were small. Never- theless, substantial economic losses were incurred due to reductions in travel and consumer spending, as well as reduced confidence in the markets.
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Design for infectious disease control in the developing world : the power of natural ventilation

Design for infectious disease control in the developing world : the power of natural ventilation

Contaminated air clearly diffuses throughout a room when the wind comes directly into the windows, rather than flowing parallel to the window openings. Air flows in a fa[r]

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Motorcycles, Cell Phones, and Electricity Can Dramatically Change the Epidemiology of Infectious Disease in Africa

Motorcycles, Cell Phones, and Electricity Can Dramatically Change the Epidemiology of Infectious Disease in Africa

In addition to the means used by microorganisms for geographic dissemination, the evolution in the means used by microorganisms for dissemination merits observation. For some authors, mobile phones can be a vector for diverse viruses (including the metapneumovirus, respiratory syncytial virus, influenza viruses, rotavirus, and norovirus), as recently demonstrated by Pillet and others, who observed a viral RNA presence on 38.5% of health-care workers ’ mobile phones. 4 A real and rapid leapfrogging has been seen in Africa, from a “no phone area” to a continent where mobile phones are widespread. It is estimated that approximately 97% of Africans will have a mobile phone by 2017, and approxi- mately 1.144 billion mobile phones have already been imported in Africa. The paradigm shift is such that in many rural areas, inhabitants had a mobile phone before elec- tricity arrived. This development will certainly change the epidemiology of infectious diseases. By extension from the results of Pillet and others, we can question the possible dis- semination of other RNA viruses using this route, and inquire about its role during the recent Ebola outbreak.
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View of New developments in infectious disease

View of New developments in infectious disease

Patients et méthodes : Tous les patients infectés par le VIH hospi- talisés dans deux services de réanimation médicale de janvier 1997 à décembre 2008 ont été inclus (un seul séjour par[r]

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Early warning of infectious disease outbreaks on cattle-transport networks

Early warning of infectious disease outbreaks on cattle-transport networks

¤ Current address: School of Mathematical Sciences, University College Cork, Cork, Ireland * beatriz.vidondo@gmx.ch Abstract Surveillance of infectious diseases in livestock is traditionally carried out at the farms, which are the typical units of epidemiological investigations and interventions. In Central and West- ern Europe, high-quality, long-term time series of animal transports have become available and this opens the possibility to new approaches like sentinel surveillance. By comparing a sentinel surveillance scheme based on markets to one based on farms, the primary aim of this paper is to identify the smallest set of sentinel holdings that would reliably and timely detect emergent disease outbreaks in Swiss cattle. Using a data-driven approach, we simu- late the spread of infectious diseases according to the reported or available daily cattle transport data in Switzerland over a four year period. Investigating the efficiency of surveil- lance at either market or farm level, we find that the most efficient early warning surveillance system [the smallest set of sentinels that timely and reliably detect outbreaks (small out- breaks at detection, short detection delays)] would be based on the former, rather than the latter. We show that a detection probability of 86% can be achieved by monitoring all 137 markets in the network. Additional 250 farm sentinels—selected according to their risk— need to be placed under surveillance so that the probability of first hitting one of these farm sentinels is at least as high as the probability of first hitting a market. Combining all markets and 1000 farms with highest risk of infection, these two levels together will lead to a detection probability of 99%. We conclude that the design of animal surveillance systems greatly ben- efits from the use of the existing abundant and detailed animal transport data especially in the case of highly dynamic cattle transport networks. Sentinel surveillance approaches can be tailored to complement existing farm risk-based and syndromic surveillance approaches.
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Coinfections in wildlife: Focus on a neglected aspect of infectious disease epidemiology

Coinfections in wildlife: Focus on a neglected aspect of infectious disease epidemiology

achieved through cross-sectional or longitudinal studies [ 6 ]. Cross-sectional studies provide information on the co-occurrence of infectious agents at the time of sampling, whereas longi- tudinal studies provide a more detailed information in the infection dynamics in individual hosts and communities over time. However, most studies designed to investigate coinfection in wildlife are restricted to limited “niches” (e.g., blood, saliva, urine, and feces), and collected samples are analyzed with targeted assays (e.g. PCR and serology), therefore, offering few opportunities to investigate generic coinfection [ 4 , 11 ]. The development and improvement of new approaches such as metagenomics, next generation sequencing, and bioinformatics, pro- vides a method to simultaneously describe a large number of pathogens without previous knowledge and a priori [ 13 , 29 , 30 ] and allow to share an increasing amount of data with the scientific community, therefore, offering new insights compared to traditional methodologies. Regarding the analytical approach, statistical tests such as chi-squared test can be used to quickly examine co-occurrence but often with limited assumptions concerning interactions and their consequences [ 6 ]. Many other statistical tests, mathematical models, and ecological theories have been developed to better infer interactions, although approaches vary depending on study designs and infectious agents [ 10 , 14 – 16 ]. Field studies can also be associated with experimental approaches such as captive studies (with wild animals) or mesocosms (artificial ecosystems) [ 14 , 22 ].
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Optimal Prevention and Elimination of Infectious Diseases

Optimal Prevention and Elimination of Infectious Diseases

1 Introduction Infectious diseases constitute major health issues for which there is large con- sensus on the legitimacy of governments interventions. Yet few analysis has been undertaken to determine the socially optimal allocation of resources to control the evolution of the disease. In this article, we derive a welfare criterion from individual preferences and give precise foundations on a generally held belief, according to which intervention should begin as soon as possible and involve large expenses. We focus our analysis on expenditure that reduce the number of contacts relevant for infection transmission per unit of time and, con- sequently, reduce the spread of the disease. They include prevention campaigns that modify individuals’ behaviors, by e.g. the di¤usion of masks or condoms that reduce the probability of a contact to be infectious, and any measures that reduce physical contacts such as lockdowns of populations. Throughout the ar- ticle, all those policies will be named as prevention measures, and the aim will be to determine the optimal intensity over time of the prevention in a economy that faces an infectious disease.
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Interdisciplinarity and Infectious Diseases: An Ebola Case Study

Interdisciplinarity and Infectious Diseases: An Ebola Case Study

Fig 1. In the two leftmost panels, we depict the hierarchy of biological organization, from molecules and genes to ecosystems. Each level of the hierarchy reflects an increase in organizational complexity, with each level being primarily composed of the previous level ’s basic units. Middle panels illustrate how the study of interactions between infectious disease agents and their hosts differs across the biomedical, public health, and ecological sciences. Specifically, biomedical sciences typically focus on lower- and medium-scale levels of biological organization (e.g., molecules, genes, and organs). In contrast, public health and ecological sciences typically focus on medium- and higher-scale levels of organization (individual, population, community, ecosystem, and environment). The filled circles and solid lines connecting the circles illustrate key cross scale biological interactions studied within each field. The right panel shows example knowledge gaps that can emerge from the “typical” segregation of research activities across the three fields. To better integrate our understanding of the causes and consequences of zoonotic infectious diseases, researchers must begin focusing on these types of missing links.
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Infectious diseases and meat production

Infectious diseases and meat production

2) Better aligning stakeholders’ incentives The first direction to reduce the zoonotic externalities of meat production, obvious for economists, consists of better aligning the stakeholders’ incentives with the common good. We first observe that the consequences of epidemics are mostly supported by the public, first through people’s morbidity and mortality and also because most financial consequences are borne by the health and public finance systems (see Section 3). Moreover, national or international agencies working on animal infectious disease prevention are usually publicly funded. In 2015, the funding for the investigation of emerging and zoonotic diseases in a single public US institution, the Centers for Disease Control, was nearly half a billion dollars (Schuck Paim and Alonso, 2020). In their survey analysis, ​Rushton and Gilbert (2016) find that more than three quarters of the cost of worldwide veterinary services for animal health are funded by the public sector. Various other induced costs of animal outbreaks such as preventive animal culling may also be a burden for the taxpayer as farmers are often compensated ex post for the economic cost of culling. Farmers also often receive subsidies for vaccines, veterinary services, and the modernization of livestock facilities, which covers biosecurity (OECD, 2017). The search and population control of wild animals living around farms is also typically carried out by public authorities; for instance, the control of African Swine Fever in South Korea was performed by the Ministry of Environment (100 persons), the Forest Service (200) and the military from five divisions (Jo and Gortazar, 2020).
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Reconciling Pasteur and Darwin to control infectious diseases

Reconciling Pasteur and Darwin to control infectious diseases

in a private correspondence with botanist Ferdinand Cohn, in which he admitted that ’if ever the origin of any infectious disease could be proved, it would be the greatest triumph to sci- ence’ (p. 234 in [ 6 ]). During Darwin’s later years and not long after his death, medical doctors in Britain brought his ideas to bear on issues such as the nature and change of infectious diseases [ 7 ]. In France, the early disciples of Pasteur (the ’Pastorians’), often depicted as Lamarckian, promoted con- cepts of selection and variation inspired by Darwinian evolutionism [ 8 ]. Historian of science Andrew Mendelsohn even describes the laboratories of Pasteur and Koch as ’the earliest place of sustained experimental cellular-level in vitro research on phenomena understood as biologi- cal variations and evolutionary mechanisms’ [ 9 ]. In retrospect, this underlying interest in varia- tion, heredity, and (possibly) evolutionary phenomena is coherent with Pasteur’s hiring of the Russian evolutionary-minded immunologist E ´lie Metchnikoff, according to whom ’the science of microbes has benefited from the application of the theory of evolution, and has made a fair return by supplying the Darwinian theory with a striking confirmation’ [ 10 ]. Furthermore, although he did not cite the work of Darwin itself, Metchnikoff’s student Charles Nicolle, direc- tor of the Pasteur Institute in Tunis for 30 years, proposed a distinctive view of the ’birth, life, and death of infectious diseases’ based on the notion of ’mutation’ in microorganisms and the assumption that human and animal populations can act as ’reservoirs’ for the emergence of new infections [ 11 ]. The idea of harnessing ecology and evolution to control infectious diseases can therefore be traced to the work of Pasteur and Darwin, even though evolutionary biology and medical microbiology have profoundly changed, both theoretically and empirically, since then. Emergence of new threats
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Nagoya Protocol and Infectious Diseases: Hindrance or Opportunity?

Nagoya Protocol and Infectious Diseases: Hindrance or Opportunity?

Keywords: pathogen sharing, Nagoya protocol on access to genetic resources and the fair and equitable sharing of benefits, infectious disease, biodiversity, social equity, global health The recent outbreak novel 2019 coronavirus (SARS-CoV-2) and the subsequent race to find its reservoir and intermediate host underline the need for swift collaborative research to be conducted all over the world. With research on infections at the animal–human interface, strong concerns have emerged in the health science community over the application of the Nagoya Protocol concerning the sharing of pathogens (and microbiota) collected from humans ( 1 – 3 ).
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Social contacts and the spread of infectious diseases

Social contacts and the spread of infectious diseases

The study of the effects of the intensity of social contacts in the epidemic diffusion, among other consequences, allows to obtain in a rigorous way a variety of non-linear incidence rates of the infectious disease as for instance recently considered in [ 34 ]. It is also interesting to remark that the presence of non-linearity in the incidence rate function, and in particular, the concavity condition with respect to the number of infected has been considered in [ 34 ] as a consequence of psychological effects. Namely, the authors observed that in the presence of a very large number of infected, the probability for an infective to transmit the virus further may decrease because the population tend to naturally reduce the number of contacts. This fact will be embedded in the kinetic model producing a change in the mean value of the number of daily contacts. The importance of reducing at best the social contacts to countering the advance of a pandemic is a well-known and studied phenomenon [ 18 ]. While in normal life activity, it is commonly assumed that a large part of agents behaves in a similar way, in presence of an extraordinary situation like the one due to a pandemic, it is highly reasonable to conjecture that the social behavior of individuals is strictly affected by their personal feeling in terms of safeness. In this work, we focus on the assumption that it is the degree of diffusion of the disease that changes people’s behavior in terms of social contacts, in view both of the personal perception and/or of the external government intervention. More generally, the model can be clearly extended to consider more realistic dependencies between an epidemic disease and the social contacts of individuals. However, this does not change the essential conclusions of our analysis, namely that there is a close interplay between the spread of the disease and the distribution of contacts, that the kinetic description is able to quantify. The encouraging results described in the rest of the article, finally suggest that a similar analysis can be carried out, at the price of an increasing difficulty in computations, in more complex epidemiological models like the SIDARTHE model [ 26 , 27 ], recently used to simulate the COVID-19 epidemic in Italy to validate and improve the eventual partial lockdown strategies of the government and to suggest future measures.
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