Dynamic transmission modeling of COVID-19 to support decision-making in Brazil: A scoping review in the pre-vaccine era.

Brazil was one of the countries most affected during the first year of the COVID-19 pandemic, in a pre-vaccine era, and mathematical and statistical models were used in decision-making and public policies to mitigate and suppress SARS-CoV-2 dispersion. In this article, we intend to overview the modeling for COVID-19 in Brazil, focusing on the first 18 months of the pandemic. We conducted a scoping review and searched for studies on infectious disease modeling methods in peer-reviewed journals and gray literature, published between January 01, 2020, and June 2, 2021, reporting real-world or scenario-based COVID-19 modeling for Brazil.

Estimating the impact of implementation and timing of the COVID-19 vaccination programme in Brazil: a counterfactual analysis.

Background: Vaccines developed between 2020 and 2021 against the SARS-CoV-2 virus were designed to diminish the severity and prevent deaths due to COVID-19. However, estimates of the effectiveness of vaccination campaigns in achieving these goals remain a methodological challenge. In this work, we developed a Bayesian statistical model to estimate the number of deaths and hospitalisations averted by vaccination of older adults (above 60 years old) in Brazil.

Modeling the impact of child vaccination (5-11 y) on overall COVID-19 related hospitalizations and mortality in a context of omicron variant predominance and different vaccination coverage paces in Brazil.

Background: Developing countries have experienced significant COVID-19 disease burden. With the emergence of new variants, particularly omicron, the disease burden in children has increased. When the first COVID-19 vaccine was approved for use in children aged 5-11 years of age, very few countries recommended vaccination due to limited risk-benefit evidence for vaccination of this population.

Modelling the impact of school reopening and contact tracing strategies on Covid-19 dynamics in different epidemiologic settings in Brazil.

We simulate the impact of school reopening during the COVID-19 pandemic in three major urban centers in Brazil to identify the epidemiological indicators and the best timing for the return of in-school activities and the effect of contact tracing as a mitigation measure. Our goal is to offer guidelines for evidence-based policymaking. We implement an extended SEIR model stratified by age and considering contact networks in different settings - school, home, work, and community, in which the infection transmission rate is affected by various intervention measures.

Modelling optimal vaccination strategies against COVID-19 in a context of Gamma variant predominance in Brazil.

Introduction: Brazil experienced moments of collapse in its health system throughout 2021, driven by the emergence of variants of concern (VOC) combined with an inefficient initial vaccination strategy against Covid-19.

Objectives: To support decision-makers in formulating COVID-19 immunization policy in the context of limited vaccine availability and evolving variants over time, we evaluate optimal strategies for Covid-19 vaccination in Brazil in 2021, when vaccination was rolled out during Gamma variant predominance.

Methods: Using a discrete-time epidemic model we estimate Covid-19 deaths averted, considering the currently Covid-19 vaccine products and doses available in Brazil; vaccine coverage by target population; and vaccine effectiveness estimates.

Model-based estimation of transmissibility and reinfection of SARS-CoV-2 P.1 variant.

Background: The SARS-CoV-2 variant of concern (VOC) P.1 (Gamma variant) emerged in the Amazonas State, Brazil, in November 2020. The epidemiological consequences of its mutations have not been widely studied, despite detection of P.

Percolation across households in mechanistic models of non-pharmaceutical interventions in SARS-CoV-2 disease dynamics.

Since the emergence of the novel coronavirus disease 2019 (COVID-19), mathematical modelling has become an important tool for planning strategies to combat the pandemic by supporting decision-making and public policies, as well as allowing an assessment of the effect of different intervention scenarios. A proliferation of compartmental models were developed by the mathematical modelling community in order to understand and make predictions about the spread of COVID-19. While compartmental models are suitable for simulating large populations, the underlying assumption of a well-mixed population might be problematic when considering non-pharmaceutical interventions (NPIs) which have a major impact on the connectivity between individuals in a population.

Spatial-temporal pattern of cutaneous leishmaniasis in Brazil.

Background: Cutaneous leishmaniasis (CL) is a vector-borne disease classified by the World Health Organization as one of the most neglected tropical diseases. Brazil has the highest incidence of CL in America and is one of the ten countries in the world with the highest number of cases. Understanding the spatiotemporal dynamics of CL is essential to provide guidelines for public health policies in Brazil.

Brazil in the face of new SARS-CoV-2 variants: emergencies and challenges in public health.

This article discusses the epidemic situation of Covid-19 in Brazil, in the face of the emergence of a new strain called P.1, which is more transmissible and may be associated with reinfection. Given the collapse of hospital care in Manaus in January 2021 and the results of three recent preprints, each that reports increased transmissibility of the P.

Climate drivers of malaria at its southern fringe in the Americas.

In this work we analyze potential environmental drivers of malaria cases in Northwestern Argentina. We inspect causal links between malaria and climatic variables by means of the convergent cross mapping technique, which provides a causality criterion from the theory of dynamic systems. Analysis is based on 12 years of weekly malaria P.

Do I Know You? How Individual Recognition Affects Group Formation and Structure.

Groups in nature can be formed by interactions between individuals, or by external pressures like predation. It is reasonable to assume that groups formed by internal and external conditions have different dynamics and structures. We propose a computational model to investigate the effects of individual recognition on the formation and structure of animal groups.

Catastrophic Regime Shift in Water Reservoirs and São Paulo Water Supply Crisis.

The relation between rainfall and water accumulated in reservoirs comprises nonlinear feedbacks. Here we show that they may generate alternative equilibrium regimes, one of high water-volume, the other of low water-volume. Reservoirs can be seen as socio-environmental systems at risk of regime shifts, characteristic of tipping point transitions.

Modeling habitat split: landscape and life history traits determine amphibian extinction thresholds.

Habitat split is a major force behind the worldwide decline of amphibian populations, causing community change in richness and species composition. In fragmented landscapes, natural remnants, the terrestrial habitat of the adults, are frequently separated from streams, the aquatic habitat of the larvae. An important question is how this landscape configuration affects population levels and if it can drive species to extinction locally.

Biodiversity can help prevent malaria outbreaks in tropical forests.

Background: Plasmodium vivax is a widely distributed, neglected parasite that can cause malaria and death in tropical areas. It is associated with an estimated 80-300 million cases of malaria worldwide. Brazilian tropical rain forests encompass host- and vector-rich communities, in which two hypothetical mechanisms could play a role in the dynamics of malaria transmission.

The role of immunity and seasonality in cholera epidemics.

This paper presents a mathematical model for cholera epidemics which comprises seasonality, loss of host immunity, and control mechanisms acting to reduce cholera transmission. A collection of data related to cholera disease allows us to show that outbreaks in endemic areas are subject to a resonant behavior, since the intrinsic oscillation period of the disease (∼1 year) is synchronized with the annual contact rate variation. Moreover, we argue that the short period of the host immunity may be associated to secondary peaks of incidence observed in some regions (a bimodal pattern).

Optimal Boussinesq model for shallow-water waves interacting with a microstructure.

In this paper, we consider the propagation of water waves in a long-wave asymptotic regime, when the bottom topography is periodic on a short length scale. We perform a multiscale asymptotic analysis of the full potential theory model and of a family of reduced Boussinesq systems parametrized by a free parameter that is the depth at which the velocity is evaluated. We obtain explicit expressions for the coefficients of the resulting effective Korteweg-de Vries (KdV) equations.

Synchronization: stability and duration time.

We consider the problem of stability and duration of the synchronization process between self-excited oscillators, both in their regular and chaotic states. Making use of the properties of Hill equation describing the deviation between the slave and the master, we derive the stability conditions and expressions of the synchronization time. A fairly good agreement is obtained between the analytical and numerical results.