MEPI-MS01

From Primate to Vectors to Humans: Understanding the underlying mechanisms of disease transmission and control

Monday, June 14 at 09:30am (PDT)
Monday, June 14 at 05:30pm (BST)
Tuesday, June 15 01:30am (KST)

SMB2021 Follow Monday (Tuesday) during the "MS01" time block.

Note: this minisymposia has multiple sessions. The second session is MS02-MEPI (click here).

Folashade Agusto (University of Kansas, United States), Majid Bani Yaghoub (University of Missouri Kansas City, United States)

Description:

Infectious diseases are a leading cause of death worldwide, particularly in low-income countries, especially in young children. Infectious diseases are caused by different agents such as bacteria, viruses, fungi, protozoa, and helminths. Some of these disease agents are transmitted through the bites of infected arthropods such as mosquitoes, ticks, and sandflies on human or primate, or simply transmitted in close quarters with an infected human. Mathematical models of infectious diseases have led to useful insight into the dynamics and control of diseases such has Zika, malaria, dengue, TB, HIV, and rabies, etc. Modeling of infectious diseases will therefore be of importance to the public health sector, and the economy. Although numerous mathematical models of infectious disease abound, deeper insight is required to understanding the dynamic nature of these diseases particularly the emerging and re-emerging diseases. It is, therefore, important to review and improve our understanding of the underlying modeling mechanisms and study approaches of these infectious diseases as well as their subsequent implications for disease control.

Amy Goldberg

(Duke University, United States)

"Model-based estimates of zoonotic malaria spillover in Atlantic Forest, Brazil"

Malaria was thought to have been eradicated from the Atlantic Coast of Brazil by the late 1970s. Previously thought to only infect non-human primates, recent molecular studies have identified the malaria parasite Plasmodium simium in humans along the Atlantic Coast of Brazil. Clinical symptoms present similarly to the common human-associated malaria parasite Plasmodium vivax, and the two parasites are difficult to distinguish with standard PCR assays or microscopy. Together, these observations raise the possibility that local monkey populations, particularly howler monkeys, act as reservoirs for zoonotic malaria that has been infecting human populations long-term. Here, we use a mathematical-modeling approach to estimate the rate of cryptic P. simiam infection that has been misdiagnosed as P. vivax in the Rio de Janiero state. We use coupled differential equations based on the Ross-MacDonald model, with two host populations representing humans and monkeys to model the infection rate of humans and howler monkeys with P. simiam. Based on elasticity analyses, we find that for the same intensity, interventions in the monkey patch reduces the overall number of human malaria cases more than interventions in the human patch. We simulate the model across a spatial grid, with the two-population system in each patch and migration between patches. Under various spillover scenarios, we compare results to clinical incidence rates of P. vivax and consider the impact on malaria elimination probability. Based on the frequency and spatial distribution of the cases, under our model, we expect spill over to be recurrent, with minimal human-to-human transmission.

Ibrahim M. ELMojtaba

(Sultan Qaboos University, Oman)

"The role of primates and human movement on the dynamics of zika virus"

We build a mathematical model to understand the role of human movement and primates in the dynamics of zika virus. The model considers the dynamics of the disease between four different populations, namely humans, primates, vectors in the rural areas, and vectors in urban areas. Our model possesses three different equilibrium, the disease-free equilibrium which is locally asymptotically stable when the basic reproduction number is less than unity, an axial equilibrium point (endemic with respect to human and vectors in urban areas, and disease-free with respect to primates and vectors in rural areas), and endemic equilibrium. The model exhibits very rich dynamics where there is a possibility of multiple bifurcations. Numerical simulations were carried out to study the effect of several parameters and to show the theoretical results.

Omar Saucedo

(Virginia Polytechnic Institute and State University, United States)

"Tick-borne Diseases in Virginia"

Ticks are known for being a source of disease infections and are cause of great concern within the public health community. Throughout the world, there are a variety of tick species that are associated with different tick-borne pathogens. Diseases such as Lyme Disease have surfaced in areas of the Commonwealth of Virginia where they previously have not been detected, and the incidence of these diseases have been steadily increasing. A better understanding of tick-borne viral pathogens is needed as this poses a threat to agriculture and livestock. In this talk, we will explore the relevant features of landscape and ecological influences on tick species and pathogen prevalence through mathematical modeling.

Sean Cavany

(University of Notre Dame, United States)

"The impacts of COVID-19 mitigation on dengue virus transmission: a modelling study"

The COVID-19 pandemic has induced unprecedented reductions in human mobility and social contacts throughout the world. Because dengue virus (DENV) transmission is strongly driven by human mobility, behavioral changes associated with the pandemic have been hypothesized to impact dengue incidence. By discouraging human contact, COVID-19 control measures have also disrupted dengue vector control interventions, the most effective of which require entry into homes. We used an agent-based model with a realistic treatment of human mobility and vector control to investigate how and why dengue incidence could differ under a lockdown scenario with a proportion of the population sheltered at home. We found that a lockdown in which 70% of the population sheltered at home led to a small average increase in cumulative DENV infections of up to 10%, depending on the time of year the lockdown occurred. Lockdown had a more pronounced effect on the spatial distribution of DENV infections, with higher incidence under lockdown in regions with high mosquito abundance. Transmission was also more focused in homes following lockdown. The proportion of people infected in their own home rose from 54% under normal conditions to 66% under lockdown, and the household secondary attack rate rose from 0.109 to 0.128, a 17% increase. When we considered that lockdown measures could disrupt regular, city-wide vector control campaigns, the increase in incidence was more pronounced than with lockdown alone, especially if lockdown occurred at the optimal time for vector control. Our results indicate that an unintended outcome of COVID-19 control measures may be to adversely alter the epidemiology of dengue. This observation has important implications for an improved understanding of dengue epidemiology and effective application of dengue vector control. When coordinating public health responses during a syndemic, it is important to monitor multiple infections and understand that an intervention against one disease may exacerbate another.

Hosted by SMB2021 Follow

Virtual conference of the Society for Mathematical Biology, 2021.