scholarly journals Mathematical modeling of COVID-19 infection dynamics in Ghana: Impact evaluation of integrated government and individual level interventions

2021 ◽  
Vol 6 ◽  
pp. 381-397
Author(s):  
Duah Dwomoh ◽  
Samuel Iddi ◽  
Bright Adu ◽  
Justice Moses Aheto ◽  
Kojo Mensah Sedzro ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Impact Evaluation ◽  
Individual Level ◽  
Infection Dynamics

Protected areas and economic welfare: an impact evaluation of national parks on local workers' wages in Costa Rica

2014 ◽  
Vol 20 (3) ◽  
pp. 283-310 ◽  
Author(s):  
Juan Robalino ◽  
Laura Villalobos
Keyword(s):  
Costa Rica ◽  
Protected Areas ◽  
National Parks ◽  
Impact Evaluation ◽  
Individual Level ◽  
Positive Effects ◽  
Level Data ◽  
Pre Treatment ◽  
Matching Techniques ◽  
Robust Evidence

AbstractThe number of protected areas around the world has significantly increased. However, the effects of this policy on the wellbeing of local households are still under debate. Using pre-treatment characteristics and household surveys with highly disaggregated geographic reference, we explore how national parks affect the wages of local workers in Costa Rica. We use matching techniques to control for the endogenous location of parks. We find that parks' effects on wages are, on average, positive and significant, but the magnitudes vary. Wages close to parks are higher for local workers living near tourist entrances. However, there is no robust evidence of positive effects for those close to parks but far away from tourist entrances. With our individual-level data, we also show that the positive effects on local households might not be as large as suggested by previous studies that use aggregated level data containing both local and immigrant households.

scholarly journals Mathematical Modelling the Impact Evaluation of Lockdown on Infection Dynamics of COVID-19 in Italy.

2020 ◽  
Author(s):  
Daniyar Yergesh ◽  
Shirali Kadyrov ◽  
Hayot Saydaliev ◽  
Alibek Orynbassar
Keyword(s):  
Policy Implementation ◽  
Impact Evaluation ◽  
Infection Dynamics ◽  
The Social ◽  
The World ◽  
Small Wave ◽  
Before And After ◽  
The Government ◽  
The Impact ◽  
Second Wave

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARSCoV-2), the cause of the coronavirus disease-2019 (COVID-19), within months of emergence from Wuhan, China, has rapidly spread, exacting a devastating human toll across around the world reaching the pandemic stage at the the beginning of March 2020. Thus, COVID-19s daily increasing cases and deaths have led to worldwide lockdown, quarantine and some restrictions. Covid-19 epidemic in Italy started as a small wave of 2 infected cases on January 31. It was followed by a bigger wave mainly from local transmissions reported in 6387 cases on March 8. It caused the government to impose a lockdown on 8 March to the whole country as a way to suppress the pandemic. This study aims to evaluate the impact of the lockdown and awareness dynamics on infection in Italy over the period of January 31 to July 17 and how the impact varies across different lockdown scenarios in both periods before and after implementation of the lockdown policy. The findings SEIR reveal that implementation lockdown has minimised the social distancing flattening the curve. The infections associated with COVID-19 decreases with quarantine initially then easing lockdown will not cause further increasing transmission until a certain period which is explained by public high awareness. Completely removing lockdown may lead to sharp transmission second wave. Policy implementation and limitation of the study were evaluated at the end of the paper. Keywords COVID-19 - Lockdown - Epidemic model - SEIR - Awareness - Dynamical systems.

scholarly journals Daily sampling of early SARS-CoV-2 infection reveals substantial heterogeneity in infectiousness

2021 ◽  
Author(s):  
Ruian Ke ◽  
Pamela P Martinez ◽  
Rebecca L Smith ◽  
Laura L Gibson ◽  
Agha Mirza ◽  
...  
Keyword(s):  
Infectious Virus ◽  
Acute Infection ◽  
Sampling Site ◽  
Virus Shedding ◽  
Individual Level ◽  
Viral Loads ◽  
Infection Dynamics ◽  
Daily Sampling ◽  
Clearance Kinetics ◽  
Longitudinal Sampling

The dynamics of SARS-CoV-2 replication and shedding in humans remain poorly understood. We captured the dynamics of infectious virus and viral RNA shedding during acute infection through daily longitudinal sampling of 60 individuals for up to 14 days. By fitting mechanistic models, we directly estimate viral reproduction and clearance rates, and overall infectiousness for each individual. Significant person-to-person variation in infectious virus shedding suggests that individual-level heterogeneity in viral dynamics contributes to superspreading. Viral genome load often peaked days earlier in saliva than in nasal swabs, indicating strong compartmentalization and suggesting that saliva may serve as a superior sampling site for early detection of infection. Viral loads and clearance kinetics of B.1.1.7 and non-B.1.1.7 viruses were indistinguishable, however B.1.1.7 exhibited a significantly slower pre-peak growth rate in saliva. These results provide a high-resolution portrait of SARS-CoV-2 infection dynamics and implicate individual-level heterogeneity in infectiousness in superspreading.

scholarly journals Persistent Plasmodium falciparum infections enhance transmission-reducing immunity development

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ruth Ayanful-Torgby ◽  
Esther Sarpong ◽  
Hamza B. Abagna ◽  
Dickson Donu ◽  
Evans Obboh ◽  
...  
Keyword(s):  
Plasmodium Falciparum ◽  
Malaria Control ◽  
Quantitative Polymerase Chain Reaction ◽  
Geographical Area ◽  
Infection Prevalence ◽  
Infection Status ◽  
Individual Level ◽  
Control Programs ◽  
Infection Dynamics ◽  
The Individual

AbstractSubclinical infections that serve as reservoir populations to drive transmission remain a hurdle to malaria control. Data on infection dynamics in a geographical area is required to strategically design and implement malaria interventions. In a longitudinal cohort, we monitored Plasmodium falciparum infection prevalence and persistence, and anti-parasite immunity to gametocyte and asexual antigens for 10 weeks. Of the 100 participants, only 11 were never infected, whilst 16 had persistent infections detected by reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR), and one participant had microscopic parasites at all visits. Over 70% of the participants were infected three or more times, and submicroscopic gametocyte prevalence was high, ≥ 48% of the parasite carriers. Naturally induced responses against recombinant Pfs48/45.6C, Pfs230proC, and EBA175RIII–V antigens were not associated with either infection status or gametocyte carriage, but the antigen-specific IgG titers inversely correlated with parasite and gametocyte densities consistent with partial immunity. Longitudinal analysis of gametocyte diversity indicated at least four distinct clones circulated throughout the study period. The high prevalence of children infected with distinct gametocyte clones coupled with marked variation in infection status at the individual level suggests ongoing transmission and should be targeted in malaria control programs.

scholarly journals Mathematical Modeling of MPNs Offers Understanding and Decision Support for Personalized Treatment

Cancers ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2119
Author(s):  
Johnny T. Ottesen ◽  
Rasmus K. Pedersen ◽  
Marc J. B. Dam ◽  
Trine A. Knudsen ◽  
Vibe Skov ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Stem Cells ◽  
Hematopoietic Stem Cells ◽  
Disease Progression ◽  
Myeloproliferative Neoplasms ◽  
Patient Specific ◽  
Hematopoietic Stem ◽  
Individual Level ◽  
Hematological Cancers ◽  
The Individual

(1) Background: myeloproliferative neoplasms (MPNs) are slowly developing hematological cancers characterized by few driver mutations, with JAK2V617F being the most prevalent. (2) Methods: using mechanism-based mathematical modeling (MM) of hematopoietic stem cells, mutated hematopoietic stem cells, differentiated blood cells, and immune response along with longitudinal data from the randomized Danish DALIAH trial, we investigate the effect of the treatment of MPNs with interferon-α2 on disease progression. (3) Results: At the population level, the JAK2V617F allele burden is halved every 25 months. At the individual level, MM describes and predicts the JAK2V617F kinetics and leukocyte- and thrombocyte counts over time. The model estimates the patient-specific treatment duration, relapse time, and threshold dose for achieving a good response to treatment. (4) Conclusions: MM in concert with clinical data is an important supplement to understand and predict the disease progression and impact of interventions at the individual level.

scholarly journals Pre-immunity: the Schrodinger's cat of immunology

2021 ◽  
Author(s):  
Marcus Carlsson ◽  
Jens Wittsten ◽  
Cecilia Soderberg-Naucler
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Theory ◽  
Population Level ◽  
Individual Variability ◽  
Great Variability ◽  
Transmission Dynamics ◽  
Large Individual ◽  
Macroscopic Scale ◽  
Individual Level ◽  
Mathematical Formulas

Early 2020, catastrophic consequences of COVID-19 was predicted in the do-nothing scenario, based on mathematical models for epidemiology. As data began to emerge, several scientists noted that growth did not seem exponential, as the models predicted, leading to speculations of pre-existing immunity or immunological dark matter to explain this pattern. On the other hand, reports of choir-rehearsals infecting most members seemed to refute this, and the topic remained inconclusive. We provide a mathematical theory in which both observations are true; on a population level, pre-immunity exists, on an individual level, it doesn't. This theory demonstrates that established formulas relating e.g. R0 and the herdimmunity threshold are wrong. We derive new mathematical formulas, which applies to any virus whose transmission dynamics is associated with large individual variability in susceptibility to the infection. Contrary to great variability in infectivity, which we show has no bearing on the mathematical modeling, variability in susceptibility actually manifests itself as pre-immunity on a macroscopic scale, thus making pre-immunity a necessity for accurate mathematical modeling.

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