Erratic flu vaccination emerges from short-sighted behavior in contact networks

The effectiveness of seasonal influenza vaccination programs depends on individual-level compliance. Perceptions about risks associated with infection and vaccination can strongly influence vaccination decisions and thus the ultimate course of an epidemic. Here we investigate the interplay between contact patterns, influenza-related behavior, and disease dynamics by incorporating game theory into network models. When individuals make decisions based on past epidemics, we find that individuals with many contacts vaccinate, whereas individuals with few contacts do not. However, the threshold number of contacts above which to vaccinate is highly dependent on the overall network structure of the population and has the potential to oscillate more wildly than has been observed empirically. When we increase the number of prior seasons that individuals recall when making vaccination decisions, behavior and thus disease dynamics become less variable. For some networks, we also find that higher flu transmission rates may, counterintuitively, lead to lower (vaccine-mediated) disease prevalence. Our work demonstrates that rich and complex dynamics can result from the interaction between infectious diseases, human contact patterns, and behavior.     

Epidemiologically Optimal Static Networks from Temporal Network Data

One of network epidemiology''s central assumptions is that the contact structure over which infectious diseases propagate can be represented as a static network. However, contacts are highly dynamic, changing at many time scales. In this paper, we investigate conceptually simple methods to construct static graphs for network epidemiology from temporal contact data. We evaluate these methods on empirical and synthetic model data. For almost all our cases, the network representation that captures most relevant information is a so-called exponential-threshold network. In these, each contact contributes with a weight decreasing exponentially with time, and there is an edge between a pair of vertices if the weight between them exceeds a threshold. Networks of aggregated contacts over an optimally chosen time window perform almost as good as the exponential-threshold networks. On the other hand, networks of accumulated contacts over the entire sampling time, and networks of concurrent partnerships, perform worse. We discuss these observations in the context of the temporal and topological structure of the data sets.     

Social Contact Networks and Disease Eradicability under Voluntary Vaccination

Certain theories suggest that it should be difficult or impossible to eradicate a vaccine-preventable disease under voluntary vaccination: Herd immunity implies that the individual incentive to vaccinate disappears at high coverage levels. Historically, there have been examples of declining coverage for vaccines, such as MMR vaccine and whole-cell pertussis vaccine, that are consistent with this theory. On the other hand, smallpox was globally eradicated by 1980 despite voluntary vaccination policies in many jurisdictions. Previous modeling studies of the interplay between disease dynamics and individual vaccinating behavior have assumed that infection is transmitted in a homogeneously mixing population. By comparison, here we simulate transmission of a vaccine-preventable SEIR infection through a random, static contact network. Individuals choose whether to vaccinate based on infection risks from neighbors, and based on vaccine risks. When neighborhood size is small, rational vaccinating behavior results in rapid containment of the infection through voluntary ring vaccination. As neighborhood size increases (while the average force of infection is held constant), a threshold is reached beyond which the infection can break through partially vaccinated rings, percolating through the whole population and resulting in considerable epidemic final sizes and a large number vaccinated. The former outcome represents convergence between individually and socially optimal outcomes, whereas the latter represents their divergence, as observed in most models of individual vaccinating behavior that assume homogeneous mixing. Similar effects are observed in an extended model using smallpox-specific natural history and transmissibility assumptions. This work illustrates the significant qualitative differences between behavior–infection dynamics in discrete contact-structured populations versus continuous unstructured populations. This work also shows how disease eradicability in populations where voluntary vaccination is the primary control mechanism may depend partly on whether the disease is transmissible only to a few close social contacts or to a larger subset of the population.     

Impact of Imitation Processes on the Effectiveness of?Ring Vaccination

Ring vaccination can be a highly effective control strategy for an emerging disease or in the final phase of disease eradication, as witnessed in the eradication of smallpox. However, the impact of behavioural dynamics on the effectiveness of ring vaccination has not been explored in mathematical models. Here, we analyze a series of stochastic models of voluntary ring vaccination. Contacts of an index case base vaccinating decisions on their own individual payoffs to vaccinate or not vaccinate, and they can also imitate the behaviour of other contacts of the index case. We find that including imitation changes the probability of containment through ring vaccination considerably. Imitation can cause a strong majority of contacts to choose vaccination in some cases, or to choose non-vaccination in other cases-even when the equivalent solution under perfectly rational (non-imitative) behaviour yields mixed choices. Moreover, imitation processes can result in very different outcomes in different stochastic realizations sampled from the same parameter distributions, by magnifying moderate tendencies toward one behaviour or the other: in some realizations, imitation causes a strong majority of contacts not to vaccinate, while in others, imitation promotes vaccination and reduces the number of secondary infections. Hence, the effectiveness of ring vaccination can depend significantly and unpredictably on imitation processes. Therefore, our results suggest that risk communication efforts should be initiated early in an outbreak when ring vaccination is to be applied, especially among subpopulations that are heavily influenced by peer opinions.     

Simulated epidemics in an empirical spatiotemporal network of 50,185 sexual contacts

Sexual contact patterns, both in their temporal and network structure, can influence the spread of sexually transmitted infections (STI). Most previous literature has focused on effects of network topology; few studies have addressed the role of temporal structure. We simulate disease spread using SI and SIR models on an empirical temporal network of sexual contacts in high-end prostitution. We compare these results with several other approaches, including randomization of the data, classic mean-field approaches, and static network simulations. We observe that epidemic dynamics in this contact structure have well-defined, rather high epidemic thresholds. Temporal effects create a broad distribution of outbreak sizes, even if the per-contact transmission probability is taken to its hypothetical maximum of 100%. In general, we conclude that the temporal correlations of our network accelerate outbreaks, especially in the early phase of the epidemics, while the network topology (apart from the contact-rate distribution) slows them down. We find that the temporal correlations of sexual contacts can significantly change simulated outbreaks in a large empirical sexual network. Thus, temporal structures are needed alongside network topology to fully understand the spread of STIs. On a side note, our simulations further suggest that the specific type of commercial sex we investigate is not a reservoir of major importance for HIV.     

Combined prime-boost vaccination against tick-borne encephalitis (TBE) using a recombinant vaccinia virus and a bacterial plasmid both expressing TBE virus non-structural NS1 protein

Background  

Heterologous prime-boost immunization protocols using different gene expression systems have proven to be successful tools in protecting against various diseases in experimental animal models. The main reason for using this approach is to exploit the ability of expression cassettes to prime or boost the immune system in different ways during vaccination procedures. The purpose of the project was to study the ability of recombinant vaccinia virus (VV) and bacterial plasmid, both carrying the NS1 gene from tick-borne encephalitis (TBE) virus under the control of different promoters, to protect mice against lethal challenge using a heterologous prime-boost vaccination protocol.     

Replicating disease spread in empirical cattle networks by adjusting the probability of infection in random networks

Comparisons between mass-action or “random” network models and empirical networks have produced mixed results. Here we seek to discover whether a simulated disease spread through randomly constructed networks can be coerced to model the spread in empirical networks by altering a single disease parameter — the probability of infection. A stochastic model for disease spread through herds of cattle is utilised to model the passage of an SEIR (susceptible–latent–infected–resistant) through five networks. The first network is an empirical network of recorded contacts, from four datasets available, and the other four networks are constructed from randomly distributed contacts based on increasing amounts of information from the recorded network. A numerical study on adjusting the value of the probability of infection was conducted for the four random network models. We found that relative percentage reductions in the probability of infection, between 5.6% and 39.4% in the random network models, produced results that most closely mirrored the results from the empirical contact networks. In all cases tested, to reduce the differences between the two models, required a reduction in the probability of infection in the random network.     

Network frailty and the geometry of herd immunity

The spread of infectious disease through communities depends fundamentally on the underlying patterns of contacts between individuals. Generally, the more contacts one individual has, the more vulnerable they are to infection during an epidemic. Thus, outbreaks disproportionately impact the most highly connected demographics. Epidemics can then lead, through immunization or removal of individuals, to sparser networks that are more resistant to future transmission of a given disease. Using several classes of contact networks-Poisson, scale-free and small-world-we characterize the structural evolution of a network due to an epidemic in terms of frailty (the degree to which highly connected individuals are more vulnerable to infection) and interference (the extent to which the epidemic cuts off connectivity among the susceptible population that remains following an epidemic). The evolution of the susceptible network over the course of an epidemic differs among the classes of networks; frailty, relative to interference, accounts for an increasing component of network evolution on networks with greater variance in contacts. The result is that immunization due to prior epidemics can provide greater community protection than random vaccination on networks with heterogeneous contact patterns, while the reverse is true for highly structured populations.     

Dynamics and Control of Diseases in Networks with Community Structure

The dynamics of infectious diseases spread via direct person-to-person transmission (such as influenza, smallpox, HIV/AIDS, etc.) depends on the underlying host contact network. Human contact networks exhibit strong community structure. Understanding how such community structure affects epidemics may provide insights for preventing the spread of disease between communities by changing the structure of the contact network through pharmaceutical or non-pharmaceutical interventions. We use empirical and simulated networks to investigate the spread of disease in networks with community structure. We find that community structure has a major impact on disease dynamics, and we show that in networks with strong community structure, immunization interventions targeted at individuals bridging communities are more effective than those simply targeting highly connected individuals. Because the structure of relevant contact networks is generally not known, and vaccine supply is often limited, there is great need for efficient vaccination algorithms that do not require full knowledge of the network. We developed an algorithm that acts only on locally available network information and is able to quickly identify targets for successful immunization intervention. The algorithm generally outperforms existing algorithms when vaccine supply is limited, particularly in networks with strong community structure. Understanding the spread of infectious diseases and designing optimal control strategies is a major goal of public health. Social networks show marked patterns of community structure, and our results, based on empirical and simulated data, demonstrate that community structure strongly affects disease dynamics. These results have implications for the design of control strategies.     

Vaccinating behaviour, information, and the dynamics of SIR vaccine preventable diseases

The increasing level of disease control by vaccination jointly with the growing standard of living and health of modern societies could favour the spread of exemption as a "rational" behaviour towards vaccination. Rational exemption implies that families will tend to relate the decision to vaccinate their children to the available information on the state of the disease. Using an SIR model with information dependent vaccination we show that rational exemption might make elimination of the disease an unfeasible task even if coverages as high as 100% are actually reached during epochs of high social alarm. Moreover, we show that rational exemption may also become responsible for the onset of sustained oscillations when the decision to vaccinate also depends on the past history of the disease.     

Does searching online for vaccination information affect vaccination coverage? Evidence from Sub-Saharan African countries

The Internet is reshaping the way people access health information. Over the past decades, an increasing number of people have been using the Internet to access vaccine-related information. Many studies suggest that the Internet can help improve people’s understanding of health issues but at the same time facilitate the rapid spread of misinformation. This study explores the impact that searching the Internet for immunization information has on vaccination coverage. Using Google trends data, we found that access to online vaccination information has impacted vaccine uptake from 2004 to 2017, in Sub-Saharan African countries. The results indicate an overall positive impact on vaccine uptake. We also found that the effects are heterogeneous among vaccines. The effect is statistically significant for the vaccine related to high-risk disease, but not significant for the controversial vaccine and the vaccine related to low-risk disease.     

Multilevel Factors Influencing Hepatitis B Screening and Vaccination among Vietnamese Americans in Atlanta,Georgia

Chronic hepatitis B virus (HBV) infection may lead to liver cirrhosis, chronic liver disease, and liver cancer. Immunization rates are suboptimal among Asian Americans/Pacific Islanders (AAPIs), who remain disproportionately affected by these illnesses. We investigated socioecological factors affecting HBV prevention among 316 Vietnamese Americans in Atlanta, Georgia. Social and community support of HBV vaccination was associated with screening (OR=1.69, 95% CI [1.21,2.38]), vaccination (OR=1.89, [1.27,2.81]), and intent to vaccinate (OR=1.77, [1.13,2.78]). Misconceptions decreased screening likelihood (OR=0.67, [0.46,0.99]) and vaccination (OR=0.55, [0.35,0.86]). Those able to pay for medical treatment (OR=1.23, [1.01,1.50]) were also more likely immunized, and greater transportation access (OR=1.42, [1.07,1.87]) was associated with greater intention to vaccinate. Multi-level factors facilitated HBV vaccination in this population. Tailored, culturally appropriate communication strategies will positively influence immunization uptake.     

Assessing metacommunity processes through signatures in spatiotemporal turnover of community composition

Although metacommunity ecology has been a major field of research in the last decades, with both conceptual and empirical outputs, the analysis of the temporal dynamics of metacommunities has only emerged recently and consists mostly of repeated static analyses. Here we propose a novel analytical framework to assess metacommunity processes using path analyses of spatial and temporal diversity turnovers. We detail the principles and practical aspects of this framework and apply it to simulated datasets to illustrate its ability to decipher the respective contributions of entangled drivers of metacommunity dynamics. We then apply it to four empirical datasets. Empirical results support the view that metacommunity dynamics may be generally shaped by multiple ecological processes acting in concert, with environmental filtering being variable across both space and time. These results reinforce our call to go beyond static analyses of metacommunities that are blind to the temporal part of environmental variability.     

Convincing the “Herd” of immunity: Lessons from smallpox vaccination in 19th century Germany

Although vaccination is a cost-effective way to control infectious diseases, it is often met with popular resistance. Studying smallpox in 19th century Germany, this paper explores how economic incentives contribute to this phenomenon. The paper adds to the literature by combining mathematical epidemiology and unpublished archival evidence from two German states - Baden and Wurttemberg. The two states are an intriguing case because their initial conditions and vaccination laws were similar. Despite this, Baden experienced lower smallpox prevalence and higher vaccination uptake than Wurttemberg. The epidemiological model predicts that incentives to vaccinate decline rapidly when immunization reduces prevalence. The archival evidence reveals that Baden offset this decline by creating a public vaccination system which reduced costs for vaccinees and vaccinators alike. This suggests that the high fixed costs of centralized immunization policies can be compensated by economies of scale and popular acceptance.     

Epidemics Scenarios in the “Romantic Network”

The networks of sexual contacts together with temporal interactions play key roles in the spread of sexually transmitted infections. Unfortunately, data for this kind of network is scarce. One of the few exceptions, the “Romantic network”, is a complete structure of a real sexual network in a high school. Based on many network measurements the authors of the work have concluded that it does not correspond to any other model network. Regarding the temporal structure, several studies indicate that relationship timing can have an effect on the diffusion throughout networks, as relationship order determines transmission routes. The aim is to check if the particular structure, static and dynamic, of the Romantic network is determinant for the propagation of an STI. We performed simulations in two scenarios: the static network where all contacts are available and the dynamic case where contacts evolve over time. In the static case, we compared the epidemic results in the Romantic network with some paradigmatic topologies. In the dynamic scenario, we considered the dynamics of formation of pairs in the Romantic network and we studied the propagation of the diseases. Our results suggest that although this real network cannot be labeled as a Watts-Strogatz network, it is, in regard to the propagation of an STI, very similar to a high disorder network. Additionally, we found that: the effect that any individual contacting an externally infected subject is to make the network closer to a fully connected one, the higher the contact degree of patient zero the faster the spread of the outbreaks, and the epidemic impact is proportional to the numbers of contacts per unit time. Finally, our simulations confirm that relationship timing severely reduced the final outbreak size, and also, show a clear correlation between the average degree and the outbreak size over time.     

Assessing immune competence in pigs by immunization with tetanus toxoid

Immune competence can be tested by challenging organisms with a set of infectious agents. However, disease control requirements impose restrictions on the infliction of infections upon domestic pigs. Alternatively, vaccinations induce detectable immune responses that reflect immune competence. Here, we tested this approach with tetanus toxoid (TT) in young domestic pigs. To optimize the vaccination protocol, we immunized the pigs with a commercial TT vaccine at the age of 21 or 35 days. Booster immunizations were performed either 14 or 21 days later. TT-specific antibodies in plasma as well as lymphoproliferative responses were determined both 7 and 14 days after booster immunization using ELISA and lymphocyte transformation tests, respectively. In addition, general IgG and IgM plasma concentrations and mitogen-induced proliferation were measured. The highest TT-specific antibody responses were detected when blood samples were collected 1 week after a booster immunization conducted 21 days after primary immunization. The pigs’ age at primary immunization did not have a significant influence on TT-specific antibody responses. Similarly, the TT-specific proliferative responses were highest when blood samples were collected 1 week after booster immunization, while age and time of primary and booster immunization were irrelevant in our setup. While general IgG and IgM plasma levels were highly age dependent, there were no significant age effects for TT-specific immune responses. In addition, mitogen-induced proliferation was independent of immunization as well as blood sampling protocols. In summary, our model of TT vaccination provides an interesting approach for the assessment of immune competence in young pigs. The detected vaccination effects were not biased by age, even though our data were acquired from immune systems that were under development during our tests.     

Susceptible-infected-recovered epidemics in dynamic contact networks

Contact patterns in populations fundamentally influence the spread of infectious diseases. Current mathematical methods for epidemiological forecasting on networks largely assume that contacts between individuals are fixed, at least for the duration of an outbreak. In reality, contact patterns may be quite fluid, with individuals frequently making and breaking social or sexual relationships. Here, we develop a mathematical approach to predicting disease transmission on dynamic networks in which each individual has a characteristic behaviour (typical contact number), but the identities of their contacts change in time. We show that dynamic contact patterns shape epidemiological dynamics in ways that cannot be adequately captured in static network models or mass-action models. Our new model interpolates smoothly between static network models and mass-action models using a mixing parameter, thereby providing a bridge between disparate classes of epidemiological models. Using epidemiological and sexual contact data from an Atlanta high school, we demonstrate the application of this method for forecasting and controlling sexually transmitted disease outbreaks.     

Infections with varying contact rates: application to varicella

We develop methods for the analysis of infectious disease data when age-specific contact rates vary over time. Our methods are valid when contact rates vary slowly on the time scale of the infection process, and are applicable to a variety of data types including serial seroprevalence surveys and case reports. The methods exploit approximate endemic equilibria, and require numerical solution of an associated integral equation in age and time. We also estimate summary statistics such as time-dependent analogs of the basic reproduction number and critical immunization threshold. We illustrate the methods with data on varicella (chickenpox) in the United Kingdom.     

Comparative immunogenicity analysis of intradermal versus intramuscular administration of SARS-CoV-2 RBD epitope peptide-based immunogen In vivo

COVID-19 pandemic has caused severe disruption of global health and devastated the socio-economic conditions all over the world. The disease is caused by SARS-CoV-2 virus that belongs to the family of Coronaviruses which are known to cause a wide spectrum of diseases both in humans and animals. One of the characteristic features of the SARS-CoV-2 virus is the high reproductive rate (R₀) that results in high transmissibility of the virus among humans. Vaccines are the best option to prevent and control this disease. Though, the traditional intramuscular (IM) route of vaccine administration is one of the effective methods for induction of antibody response, a needle-free self-administrative intradermal (ID) immunization will be easier for SARS-CoV-2 infection containment, as vaccine administration method will limit human contacts. Here, we have assessed the humoral and cellular responses of a RBD-based peptide immunogen when administered intradermally in BALB/c mice and side-by-side compared with the intramuscular immunization route. The results demonstrate that ID vaccination is well tolerated and triggered a significant magnitude of humoral antibody responses as similar to IM vaccination. Additionally, the ID immunization resulted in higher production of IFN-γ and IL-2 suggesting superior cellular response as compared to IM route. Overall, our data indicates immunization through ID route provides a promising alternative approach for the development of self-administrative SARS-CoV-2 vaccine candidates.