Shorter Infectious Period Research Articles

The lived experience of long COVID: A qualitative study of mental health, quality of life, and coping.

The majority of people who contract COVID-19 experience a short period of symptomatic infection. However, symptoms persist for months or years following initial exposure to the virus in some cases. This has been described as long COVID. Little is known about the lived experience of this condition, as it has only recently emerged. This study aimed to explore the experiences of mental health, quality of life, and coping among people living with long COVID. A sample of 47 adults with lived experience participated in web-based focus groups. Separate focus groups were held for 24 individuals with pre-existing mental health conditions and 23 individuals without pre-existing mental health conditions. Data were analyzed using a codebook thematic analysis approach. Five themes were identified as integral to the long COVID experience: The Emotional Landscape of Long COVID, New Limits to Daily Functioning, Grief and Loss of Former Identity, Long COVID-related Stigmatization, and Learning to Cope with Persisting Symptoms. These findings illustrate the immense impact of long COVID on mental health and quality of life. Minimal differences were found between those with and those without pre-existing mental health conditions, as both groups were substantially impacted by the condition. Attention to the perspectives of people with lived experience of long COVID is necessary to inform future directions for research and clinical practice.

Contact-number-driven virus evolution: A multi-level modeling framework for the evolution of acute or persistent RNA virus infection.

Viruses evolve in infected host populations, and host population dynamics affect viral evolution. RNA viruses with a short duration of infection and a high peak viral load, such as SARS-CoV-2, are maintained in human populations. By contrast, RNA viruses characterized by a long infection duration and a low peak viral load (e.g., borna disease virus) can be maintained in nonhuman populations, and the process of the evolution of persistent viruses has rarely been explored. Here, using a multi-level modeling approach including both individual-level virus infection dynamics and population-scale transmission, we consider virus evolution based on the host environment, specifically, the effect of the contact history of infected hosts. We found that, with a highly dense contact history, viruses with a high virus production rate but low accuracy are likely to be optimal, resulting in a short infectious period with a high peak viral load. In contrast, with a low-density contact history, viral evolution is toward low virus production but high accuracy, resulting in long infection durations with low peak viral load. Our study sheds light on the origin of persistent viruses and why acute viral infections but not persistent virus infection tends to prevail in human society.

The pitfalls of inferring virus-virus interactions from co-detection prevalence data: application to influenza and SARS-CoV-2.

There is growing experimental evidence that many respiratory viruses—including influenza and SARS-CoV-2—can interact, such that their epidemiological dynamics may not be independent. To assess these interactions, standard statistical tests of independence suggest that the prevalence ratio—defined as the ratio of co-infection prevalence to the product of single-infection prevalences—should equal unity for non-interacting pathogens. As a result, earlier epidemiological studies aimed to estimate the prevalence ratio from co-detection prevalence data, under the assumption that deviations from unity implied interaction. To examine the validity of this assumption, we designed a simulation study that built on a broadly applicable epidemiological model of co-circulation of two emerging or seasonal respiratory viruses. By focusing on the pair influenza–SARS-CoV-2, we first demonstrate that the prevalence ratio systematically underestimates the strength of interaction, and can even misclassify antagonistic or synergistic interactions that persist after clearance of infection. In a global sensitivity analysis, we further identify properties of viral infection—such as a high reproduction number or a short infectious period—that blur the interaction inferred from the prevalence ratio. Altogether, our results suggest that ecological or epidemiological studies based on co-detection prevalence data provide a poor guide to assess interactions among respiratory viruses.

Complete genome characterization of human noroviruses allows comparison of minor alleles during acute and chronic infections.

Human noroviruses (HuNoVs) circulate globally, affect all age groups and place a substantial burden upon health services. High genetic diversity leading to antigenic variation plays a significant role in HuNoV epidemiology, driving periodic global emergence of epidemic variants. Studies have suggested that immunocompromised individuals may be a reservoir for such epidemic variants, but studies investigating the diversity and emergence of HuNoV variants in immunocompetent individuals are underrepresented. To address this, we sequenced the genomes of HuNoVs present in samples collected longitudinally from one immunocompetent (acute infection) and one immunocompromised (chronic infection) patient. A broadly reactive HuNoV capture-based method was used to concentrate the virus present in these specimens prior to massively parallel sequencing to recover near complete viral genomes. Using a novel bioinformatics pipeline, we demonstrated that persistent minor alleles were present in both acute and chronic infections, and that minor allele frequencies represented a larger proportion of the population during chronic infection. In acute infection, minor alleles were more evenly spread across the genome, although present at much lower frequencies, and therefore difficult to discern from error. By contrast, in the chronic infection, more minor alleles were present in the minor structural protein. No non-synonymous minor alleles were detected in the major structural protein over the short sampling period of the HuNoV chronic infection, suggesting where immune pressure is variable or non-existent, epidemic variants could emerge over longer periods of infection by random chance.

Alzheimer's Disease-Like Pathology Triggered by Porphyromonas gingivalis in Wild Type Rats Is Serotype Dependent.

Periodontal disease is a disease of tooth-supporting tissues. It is a chronic disease with inflammatory nature and infectious etiology produced by a dysbiotic subgingival microbiota that colonizes the gingivodental sulcus. Among several periodontal bacteria, Porphyromonas gingivalis (P. gingivalis) highlights as a keystone pathogen. Previous reports have implied that chronic inflammatory response and measurable bone resorption are observed in young mice, even after a short period of periodontal infection with P. gingivalis, which has been considered as a suitable model of experimental periodontitis. Also, encapsulated P. gingivalis strains are more virulent than capsular-defective mutants, causing an increased immune response, augmented osteoclastic activity, and accrued alveolar bone resorption in these rodent experimental models of periodontitis. Recently, P. gingivalis has been associated with Alzheimer’s disease (AD) pathogenesis, either by worsening brain pathology in AD-transgenic mice or by inducing memory impairment and age-dependent neuroinflammation middle-aged wild type animals. We hypothesized here that the more virulent encapsulated P. gingivalis strains could trigger the appearance of brain AD-markers, neuroinflammation, and cognitive decline even in young rats subjected to a short periodontal infection exposure, due to their higher capacity of activating brain inflammatory responses. To test this hypothesis, we periodontally inoculated 4-week-old male Sprague-Dawley rats with K1, K2, or K4 P. gingivalis serotypes and the K1-isogenic non-encapsulated mutant (GPA), used as a control. 45-days after periodontal inoculations with P. gingivalis serotypes, rat´s spatial memory was evaluated for six consecutive days in the Oasis maze task. Following functional testing, the animals were sacrificed, and various tissues were removed to analyze alveolar bone resorption, cytokine production, and detect AD-specific biomarkers. Strikingly, only K1 or K2 P. gingivalis-infected rats displayed memory deficits, increased alveolar bone resorption, pro-inflammatory cytokine production, changes in astrocytic morphology, increased Aβ1-42 levels, and Tau hyperphosphorylation in the hippocampus. None of these effects were observed in rats infected with the non-encapsulated bacterial strains. Based on these results, we propose that the bacterial virulence factors constituted by capsular polysaccharides play a central role in activating innate immunity and inflammation in the AD-like pathology triggered by P. gingivalis in young rats subjected to an acute experimental infection episode.

Forecasting the outcome and estimating the epidemic model parameters from the fatality time series in COVID-19 outbreaks

In the absence of other tools, monitoring the effects of protective measures, including social distancing and forecasting the outcome of outbreaks is of immense interest. Real-time data is noisy and very often hampered by systematic errors in reporting. Detailed epidemic models may contain a large number of empirical parameters, which cannot be determined with sufficient accuracy. In this paper, we show that the cumulative number of deaths can be regarded as a master variable, and the parameters of the epidemic such as the basic reproduction number, the size of the susceptible population, and the infection rate can be determined. In the SIR model, we derive an explicit single variable differential equation for the evolution of the cumulative number of fatalities. We show that the epidemic in Spain, Italy, and Hubei Province, China follows this master equation closely. We discuss the relationship with the logistic growth model, and we show that it is a good approximation when the basic reproduction number is less than 2.3. This condition is valid for the outbreak in Hubei, but not for the outbreaks in Spain, Italy, and New York. The difference is in the shorter infectious period in China, probably due to the separation policy of the infected. For more complex models, with more internal variables, such as the SEIR model, the equations derived from the SIR model remain valid approximately, due to the separation of timescales.

Reactivation of latent infections with migration shapes population-level disease dynamics.

Annual migration is common across animal taxa and can dramatically shape the spatial and temporal patterns of infectious disease. Although migration can decrease infection prevalence in some contexts, these energetically costly long-distance movements can also have immunosuppressive effects that may interact with transmission processes in complex ways. Here, we develop a mechanistic model for the reactivation of latent infections driven by physiological changes or energetic costs associated with migration (i.e. 'migratory relapse') and its effects on disease dynamics. We determine conditions under which migratory relapse can amplify or reduce infection prevalence across pathogen and host traits (e.g. infectious periods, virulence, overwinter survival, timing of relapse) and transmission phenologies. We show that relapse at either the start or end of migration can dramatically increase prevalence across the annual cycle and may be crucial for maintaining pathogens with low transmissibility and short infectious periods in migratory populations. Conversely, relapse at the start of migration can reduce the prevalence of highly virulent pathogens by amplifying culling of infected hosts during costly migration, especially for highly transmissible pathogens and those transmitted during migration or the breeding season. Our study provides a mechanistic foundation for understanding the spatio-temporal patterns of relapsing infections in migratory hosts, with implications for zoonotic surveillance and understanding how infection patterns will respond to shifts in migratory propensity associated with environmental change. Further, our work suggests incorporating within-host processes into population-level models of pathogen transmission may be crucial for reconciling the range of migration-infection relationships observed across migratory species.

A large effective population size for established within-host influenza virus infection.

Strains of the influenza virus form coherent global populations, yet exist at the level of single infections in individual hosts. The relationship between these scales is a critical topic for understanding viral evolution. Here we investigate the within-host relationship between selection and the stochastic effects of genetic drift, estimating an effective population size of infection Ne for influenza infection. Examining whole-genome sequence data describing a chronic case of influenza B in a severely immunocompromised child we infer an Ne of 2.5 × 107 (95% confidence range 1.0 × 107 to 9.0 × 107) suggesting that genetic drift is of minimal importance during an established influenza infection. Our result, supported by data from influenza A infection, suggests that positive selection during within-host infection is primarily limited by the typically short period of infection. Atypically long infections may have a disproportionate influence upon global patterns of viral evolution.

Implementation of Power Law Network Models of Epidemic Surveillance Data for Better Evaluation of Outbreak Detection Alarms

Abstract Properties of statistical alarms have been well studied for simple disease surveillance models, such as normally distributed incidence rates with a sudden or gradual shift in mean at the start of an outbreak. It is known, however, that outbreak dynamics in human populations depend significantly on the heterogeneity of the underlying contact network. The rate of change in incidence for a disease such as influenza peaks early on during the outbreak, when the most highly connected individuals get infected, and declines as the average number of connections in the remaining susceptible population drops. Alarm systems currently in use for detecting the start of influenza seasons generally ignore this mechanism of disease spread, and, as a result, will miss out on some early warning signals. We investigate the performance of various alarms on epidemics simulated from an undirected network model with a power law degree distribution for a pathogen with a relatively short infectious period. We propose simple custom alarms for the disease system considered, and show that they can detect a change in the process sooner than some traditional alarms. Finally, we test our methods on observed rates of influenza-like illness from two sentinel providers (one French, one Spanish) to illustrate their use in the early detection of the flu season.

Large-scale analysis of herpesviridae in epilepsy-patients with signs of autoimmune encephalitis

PurposeEpilepsy is one of the most common primary brain disorders. Nonparaneoplastic autoimmune encephalitis is increasingly recognized as an important cause of adult onset epilepsy. However, only in rare cases an initiating factor of the syndrome can be identified. Autoantibody detection after central nervous herpesvirus infection indicates a postviral etiology in a subgroup of patients. In order to analyze a possible underrecognition of postinfectious autoimmunity we performed a large-scale analysis of herpesvirus DNA in cerebrospinal fluid samples from patients with clinical signs of autoimmune encephalitis. MethodsReal time PCR for HSV 1/2, CMV, EBV, VZV, HHV-6A, HHV-6B, HHV-7 and HHV-8 was performed in cerebrospinal fluid samples from 113 patients with epilepsy and suspected autoimmune encephalitis. Indirect immunofluorescence analysis was used for autoantibody analysis. ResultsAntineuronal autoantibodies could be identified in 48 patients with definite autoimmune encephalitis. No autoantibodies were detected in 65 additional patients with probable or possible autoimmune encephalitis. Real-time PCR analysis revealed in three autoantibody-negative patients positive results for HSV, but no evidence for further virus DNA. ConclusionThe findings argue against longstanding herpesvirus infection of the CNS as frequent trigger for autoimmunity. However, appearance of autoantibodies after a short period of active virus infection cannot be excluded.

The lifecycle of Dichelyne minutus (Rudolphi, 1819) (Nematoda: Cucullanidae) in the estuarine biocenosis of the Black Sea

The lifecycle, the host–parasite system, and the ecological features of the nematode Dichelyne minutus (Rudolphi, 1819), which parasitizes invertebrates and fish in the estuarine biocenosis located at the influx of the Chornaya River into the Black Sea (off Sevastopol), have been studied. The host–parasite system of D. minutus includes the polychaete Hediste diversicolor Muller, 1776 (as an obligatory intermediate host) and nine fish species, of which seven are definitive hosts and two are accidental or captive hosts. It has been found that the lifecycle of D. minutus in the biocoenosis of the Black Sea differs from the lifecycle of this nematode that inhabits the Baltic and North seas. In the studied biocoenosis, nematode larvae occur in polychaetes and fish only in the spring and summer; no larvae are found in the autumn (the study was not conducted in the winter). The nematode parasitizes the polychaete H. diversicolor in the spring; the main source of infection in this period is obviously nematode eggs that were laid in the autumn and have overwintered in the environment. The infection process ends by early summer. The seasonal and size–age dynamics of nematode infection of the round goby, Neogobius melanostomus (Pallas, 1814), are analyzed taking the specifics of fish biology into account. The short period of infection, as characterized by the active emission of nematode larvae, their low survival in polychaetes and fish, a short lifecycle and the mortality of mature nematodes after egg-laying in the autumn result in an over-scattered distribution (mostly of the negative-binomial type) of D. minutus in populations of all the hosts.

Controlling infectious disease through the targeted manipulation of contact network structure

Individuals in human and animal populations are linked through dynamic contact networks with characteristic structural features that drive the epidemiology of directly transmissible infectious diseases. Using animal movement data from the British cattle industry as an example, this analysis explores whether disease dynamics can be altered by placing targeted restrictions on contact formation to reconfigure network topology. This was accomplished using a simple network generation algorithm that combined configuration wiring with stochastic block modelling techniques to preserve the weighted in- and out-degree of individual nodes (farms) as well as key demographic characteristics of the individual network connections (movement date, livestock market, and animal production type). We then tested a control strategy based on introducing additional constraints into the network generation algorithm to prevent farms with a high in-degree from selling cattle to farms with a high out-degree as these particular network connections are predicted to have a disproportionately strong role in spreading disease. Results from simple dynamic disease simulation models predicted significantly lower endemic disease prevalences on the trade restricted networks compared to the baseline generated networks. As expected, the relative magnitude of the predicted changes in endemic prevalence was greater for diseases with short infectious periods and low transmission probabilities. Overall, our study findings demonstrate that there is significant potential for controlling multiple infectious diseases simultaneously by manipulating networks to have more epidemiologically favourable topological configurations. Further research is needed to determine whether the economic and social benefits of controlling disease can justify the costs of restricting contact formation.

The effect of seasonal birth pulses on pathogen persistence in wild mammal populations.

The notion of a critical community size (CCS), or population size that is likely to result in long-term persistence of a communicable disease, has been developed based on the empirical observations of acute immunizing infections in human populations, and extended for use in wildlife populations. Seasonal birth pulses are frequently observed in wildlife and are expected to impact infection dynamics, yet their effect on pathogen persistence and CCS have not been considered. To investigate this issue theoretically, we use stochastic epidemiological models to ask how host life-history traits and infection parameters interact to determine pathogen persistence within a closed population. We fit seasonal birth pulse models to data from diverse mammalian species in order to identify realistic parameter ranges. When varying the synchrony of the birth pulse with all other parameters being constant, our model predicted that the CCS can vary by more than two orders of magnitude. Tighter birth pulses tended to drive pathogen extinction by creating large amplitude oscillations in prevalence, especially with high demographic turnover and short infectious periods. Parameters affecting the relative timing of the epidemic and birth pulse peaks determined the intensity and direction of the effect of pre-existing immunity in the population on the pathogen's ability to persist beyond the initial epidemic following its introduction.

Transfusion transmission risk of dengue viruses in an endemic area

It is believed that dengue virus (DENV) is transfusion transmittable, only a few transfusion associated cases were reported so far in spite of at least 50 million dengue infections occur globally each year. The equation for calculating DENV transfusion transmission probability was proposed following the West Nile Virus model. In consideration of reported case number, population size in the region around the designated cases, symptomatic infection rate, blood donation rate, and mosquito biological characteristics together, a relative low rate of DENV transmittable donations was presumed in a low‐grade endemic area. Both the apparent clinical presentation and the relative short viremia period of DENV infection prevent dengue viruses from being a highly potential transfusion transmittable agent. The geographically based selection and donor deferral strategy seems to effectively mitigate the potential risk of DENV transfusion transmission. The costly minipooled nucleic acid test (NAT) is therefore not recommended unless for ensuring enough safe blood donations in the dengue epidemic area.

Transmission and Control of African Horse Sickness in The Netherlands: A Model Analysis

African horse sickness (AHS) is an equine viral disease that is spread by Culicoides spp. Since the closely related disease bluetongue established itself in The Netherlands in 2006, AHS is considered a potential threat for the Dutch horse population. A vector-host model that incorporates the current knowledge of the infection biology is used to explore the effect of different parameters on whether and how the disease will spread, and to assess the effect of control measures. The time of introduction is an important determinant whether and how the disease will spread, depending on temperature and vector season. Given an introduction in the most favourable and constant circumstances, our results identify the vector-to-host ratio as the most important factor, because of its high variability over the country. Furthermore, a higher temperature accelerates the epidemic, while a higher horse density increases the extent of the epidemic. Due to the short infectious period in horses, the obvious clinical signs and the presence of non-susceptible hosts, AHS is expected to invade and spread less easily than bluetongue. Moreover, detection is presumed to be earlier, which allows control measures to be targeted towards elimination of infection sources. We argue that recommended control measures are euthanasia of infected horses with severe clinical signs and vector control in infected herds, protecting horses from midge bites in neighbouring herds, and (prioritized) vaccination of herds farther away, provided that transport regulations are strictly applied. The largest lack of knowledge is the competence and host preference of the different Culicoides species present in temperate regions.

Viruses That Cross Borders: Factors Responsible for Global Dissemination of Viral Infections

Objective: Pandemic viral infections as emerging infectious diseases are of a great global concern. However, for some viruses, particular strains are endemic to specific areas and can be genetically distinguished from strains in other regions. In contrast, for some other viruses, genetically similar strains can spread and circulate all over the world. This study addresses global dissemination of various viral infections. Methods: We classified 34 viruses as per their ability to cross borders by review. We also described factors responsible for and the dynamics of global dissemination. We examined biological characteristics of viruses, manners or routes of transmission, host responses and epidemiological factors. Results: Factors required for viruses to cross borders include ‘non-blood infection’, ‘short incubation period’, ‘short infectious period’, ‘frequent re-infection’, ‘small basic reproductive number (R₀)’ and ‘high annual incidence’. Conclusion: Knowing the factors responsible for global dissemination of pathogens is useful for controlling and/or containing both classic and emerging infectious diseases.

Potential for epidemic take-off from the primary outbreak farm via livestock movements

BackgroundWe consider the potential for infection to spread in a farm population from the primary outbreak farm via livestock movements prior to disease detection. We analyse how this depends on the time of the year infection occurs, the species transmitting, the length of infectious period on the primary outbreak farm, location of the primary outbreak, and whether a livestock market becomes involved. We consider short infectious periods of 1 week, 2 weeks and 4 weeks, characteristic of acute contagious livestock diseases. The analysis is based on farms in Scotland from 1 January 2003 to 31 July 2007.ResultsThe proportion of primary outbreaks from which an acute contagious disease would spread via movement of livestock is generally low, but exhibits distinct annual cyclicity with peaks in May and August. The distance that livestock are moved varies similarly: at the time of the year when the potential for spread via movements is highest, the geographical spread via movements is largest. The seasonal patterns for cattle differ from those for sheep whilst there is no obvious seasonality for pigs. When spread via movements does occur, there is a high risk of infection reaching a livestock market; infection of markets can amplify disease spread. The proportion of primary outbreaks that would spread infection via livestock movements varies significantly between geographical regions.ConclusionsIn this paper we introduce a set-up for analysis of movement data that allows for a generalized assessment of the risk associated with infection spreading from a primary outbreak farm via livestock movements, applying this to Scotland, we assess how this risk depends upon the time of the year, species transmitting, location of the farm and other factors.

Disease transmission in territorial populations: the small-world network of Serengeti lions.

Territoriality in animal populations creates spatial structure that is thought to naturally buffer disease invasion. Often, however, territorial populations also include highly mobile, non-residential individuals that potentially serve as disease superspreaders. Using long-term data from the Serengeti Lion Project, we characterize the contact network structure of a territorial wildlife population and address the epidemiological impact of nomadic individuals. As expected, pride contacts are dominated by interactions with neighbouring prides and interspersed by encounters with nomads as they wander throughout the ecosystem. Yet the pride-pride network also includes occasional long-range contacts between prides, making it surprisingly small world and vulnerable to epidemics, even without nomads. While nomads increase both the local and global connectivity of the network, their epidemiological impact is marginal, particularly for diseases with short infectious periods like canine distemper virus. Thus, territoriality in Serengeti lions may be less protective and non-residents less important for disease transmission than previously considered.

Models of epidemics: when contact repetition and clustering should be included

Background: The spread of infectious disease is determined by biological factors, e.g. the duration of the infectious period, and social factors, e.g. the arrangement of potentially contagious contacts. Repetitiveness and clustering of contacts are known to be relevant factors influencing the transmission of droplet or contact transmitted diseases. Yet unknown is however how these factors are included at best in models of disease spread. Methods: We compare two different types of individual-based models: One assumes random mixing without repetition of contacts, whereas the other assumes that the same contacts repeat day-by-day. The latter exists in two variants, with and without clustering. We systematically test and compare how the total size of an outbreak differs between these model types depending on the key parameters transmission probability, number of contacts per day, duration of the infectious period, different levels of clustering and varying proportions of repetitive contacts. Results: The difference between both model types is highest for low numbers of contacts per day and low transmission probabilities. The number of contacts and the transmission probability have a higher influence on this difference than the duration of the infectious period. Even when only minor parts of the daily contacts are repetitive and clustered can there be relevant differences compared to a purely random mixing model. Conclusion: We show that random mixing models provide acceptable estimates of the total outbreak size if the number of contacts per day is high or if the per-contact transmission probability is high, as in measles. In the case of very short infectious periods, as in Norovirus, models assuming repeating contacts will also behave similarly as random mixing models. If the number of daily contacts or the transmission probability is low, particular consideration should be given to the actual structure of potentially contagious contacts when designing the model.

Persistence of Pathogens with Short Infectious Periods in Seasonal Tick Populations: The Relative Importance of Three Transmission Routes

BackgroundThe flaviviruses causing tick-borne encephalitis (TBE) persist at low but consistent levels in tick populations, despite short infectious periods in their mammalian hosts and transmission periods constrained by distinctly seasonal tick life cycles. In addition to systemic and vertical transmission, cofeeding transmission has been proposed as an important route for the persistence of TBE-causing viruses. Because cofeeding transmission requires ticks to feed simultaneously, the timing of tick activity may be critical to pathogen persistence. Existing models of tick-borne diseases do not incorporate all transmission routes and tick seasonality. Our aim is to evaluate the influence of seasonality on the relative importance of different transmission routes by using a comprehensive mathematical model.Methodology/Principal FindingsWe developed a stage-structured population model that includes tick seasonality and evaluated the relative importance of the transmission routes for pathogens with short infectious periods, in particular Powassan virus (POWV) and the related “deer tick virus,” emergent encephalitis-causing flaviviruses in North America. We used the next generation matrix method to calculate the basic reproductive ratio and performed elasticity analyses. We confirmed that cofeeding transmission is critically important for such pathogens to persist in seasonal tick populations over the reasonable range of parameter values. At higher but still plausible rates of vertical transmission, our model suggests that vertical transmission can strongly enhance pathogen prevalence when it operates in combination with cofeeding transmission.Conclusions/SignificanceOur results demonstrate that the consistent prevalence of POWV observed in tick populations could be maintained by a combination of low vertical, intermediate cofeeding and high systemic transmission rates. When vertical transmission is weak, nymphal ticks support integral parts of the transmission cycle that are critical for maintaining the pathogen. We also extended the model to pathogens that cause chronic infections in hosts and found that cofeeding transmission could contribute to elevating prevalence even in these systems. Therefore, the common assumption that cofeeding transmission is not relevant in models of chronic host infection, such as Lyme disease, could lead to underestimating pathogen prevalence.