7 research outputs found
Estimating the reproductive number, total outbreak size, and reporting rates for Zika epidemics in South and Central America
As South and Central American countries prepare for increased birth defects
from Zika virus outbreaks and plan for mitigation strategies to minimize
ongoing and future outbreaks, understanding important characteristics of Zika
outbreaks and how they vary across regions is a challenging and important
problem. We developed a mathematical model for the 2015 Zika virus outbreak
dynamics in Colombia, El Salvador, and Suriname. We fit the model to publicly
available data provided by the Pan American Health Organization, using
Approximate Bayesian Computation to estimate parameter distributions and
provide uncertainty quantification. An important model input is the at-risk
susceptible population, which can vary with a number of factors including
climate, elevation, population density, and socio-economic status. We informed
this initial condition using the highest historically reported dengue incidence
modified by the probable dengue reporting rates in the chosen countries. The
model indicated that a country-level analysis was not appropriate for Colombia.
We then estimated the basic reproduction number, or the expected number of new
human infections arising from a single infected human, to range between 4 and 6
for El Salvador and Suriname with a median of 4.3 and 5.3, respectively. We
estimated the reporting rate to be around 16% in El Salvador and 18% in
Suriname with estimated total outbreak sizes of 73,395 and 21,647 people,
respectively. The uncertainty in parameter estimates highlights a need for
research and data collection that will better constrain parameter ranges.Comment: 35 pages, 16 figure
Prediction and Optimal Scheduling of Advertisements in Linear Television
Advertising is a crucial component of marketing and an important way for companies to raise awareness of goods and services in the marketplace. Advertising campaigns are designed to convey a marketing image or message to an audience of potential consumers and television commercials can be an effective way of transmitting these messages to a large audience. In order to meet the requirements for a typical advertising order, television content providers must provide advertisers with a predetermined number of impressions in the target demographic. However, because the number of impressions for a given program is not known a priori and because there are a limited number of time slots available for commercials, scheduling advertisements efficiently can be a challenging computational problem. In this case study, we compare a variety of methods for estimating future viewership patterns in a target demographic from past data. We also present a method for using those predictions to generate an optimal advertising schedule that satisfies campaign requirements while maximizing advertising revenue
Prediction and Optimal Scheduling of Advertisements in Linear Television
Advertising is a crucial component of marketing and an important way for companies to raise awareness of goods and services in the marketplace. Advertising campaigns are designed to convey a marketing image or message to an audience of potential consumers and television commercials can be an effective way of transmitting these messages to a large audience. In order to meet the requirements for a typical advertising order, television content providers must provide advertisers with a predetermined number of impressions in the target demographic. However, because the number of impressions for a given program is not known a priori and because there are a limited number of time slots available for commercials, scheduling advertisements efficiently can be a challenging computational problem. In this case study, we compare a variety of methods for estimating future viewership patterns in a target demographic from past data. We also present a method for using those predictions to generate an optimal advertising schedule that satisfies campaign requirements while maximizing advertising revenue