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1.
Am Nat ; 204(2): 133-146, 2024 Aug.
Article in English | MEDLINE | ID: mdl-39008835

ABSTRACT

AbstractInfectious disease dynamics operate across biological scales: pathogens replicate within hosts but transmit among populations. Functional changes in the pathogen-host interaction thus generate cascading effects across organizational scales. We investigated within-host dynamics and among-host transmission of three strains (SAT-1, -2, -3) of foot-and-mouth disease viruses (FMDVs) in their wildlife host, African buffalo. We combined data on viral dynamics and host immune responses with mathematical models to ask the following questions: How do viral and immune dynamics vary among strains? Which viral and immune parameters determine viral fitness within hosts? And how do within-host dynamics relate to virus transmission? Our data reveal contrasting within-host dynamics among viral strains, with SAT-2 eliciting more rapid and effective immune responses than SAT-1 and SAT-3. Within-host viral fitness was overwhelmingly determined by variation among hosts in immune response activation rates but not by variation among individual hosts in viral growth rate. Our analyses investigating across-scale linkages indicate that viral replication rate in the host correlates with transmission rates among buffalo and that adaptive immune activation rate determines the infectious period. These parameters define the virus's relative basic reproductive number (ℛ0), suggesting that viral invasion potential may be predictable from within-host dynamics.


Subject(s)
Buffaloes , Foot-and-Mouth Disease Virus , Foot-and-Mouth Disease , Animals , Buffaloes/virology , Foot-and-Mouth Disease Virus/immunology , Foot-and-Mouth Disease Virus/growth & development , Foot-and-Mouth Disease/transmission , Foot-and-Mouth Disease/virology , Foot-and-Mouth Disease/immunology , Host-Pathogen Interactions/immunology , Virus Replication , Models, Biological
2.
J Theor Biol ; 532: 110919, 2022 01 07.
Article in English | MEDLINE | ID: mdl-34592263

ABSTRACT

The COVID-19 pandemic has led to widespread attention given to the notions of "flattening the curve" during lockdowns, and successful contact tracing programs suppressing outbreaks. However a more nuanced picture of these interventions' effects on epidemic trajectories is necessary. By mathematical modeling each as reactive quarantine measures, dependent on current infection rates, with different mechanisms of action, we analytically derive distinct nonlinear effects of these interventions on final and peak outbreak size. We simultaneously fit the model to provincial reported case and aggregated quarantined contact data from China. Lockdowns compressed the outbreak in China inversely proportional to population quarantine rates, revealing their critical dependence on timing. Contact tracing had significantly less impact on final outbreak size, but did lead to peak size reduction. Our analysis suggests that altering the cumulative cases in a rapidly spreading outbreak requires sustained interventions that decrease the reproduction number close to one, otherwise some type of swift lockdown measure may be needed.


Subject(s)
COVID-19 , Contact Tracing , China/epidemiology , Communicable Disease Control , Disease Outbreaks/prevention & control , Humans , Pandemics , Quarantine , SARS-CoV-2
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