Optimizing Vaccine Allocation at Different Points in Time during an Epidemic

For current pandemic influenza H1N1, vaccine production started in the early summer, and vaccination started in the fall. In most countries, by the time vaccination started, the second wave of H1N1 was already under way. With limited supplies of vaccine, it might be a good strategy to vaccinate the high-transmission groups earlier in the epidemic, but it might be a better use of resources to protect instead the high-risk groups later on. We develop a deterministic epidemic model with two age-groups (children and adults) and further subdivide each age group in low and high risk. We compare optimal vaccination strategies started at various points in time in two different settings: a population in the United States (US) where children account for 24% of the population, and a population in Senegal, where children make up for the majority of the population, 55%. For each of these populations, we minimize mortality and we find an optimal vaccination vector that gives us the best vaccine allocation given a starting vaccination date and vaccine coverage level. We find that there is a switch in the optimal vaccination strategy at some time point just before the peak of the epidemic. For instance, with 25% vaccine coverage, it is better to protect the high-transmission groups before this point, but it is optimal to protect the most vulnerable groups afterward

Achieving coordinated national immunity and cholera elimination in Haiti through vaccination: a modelling study

Summary: Background: Cholera was introduced into Haiti in 2010. Since then, more than 820 000 cases and nearly 10 000 deaths have been reported. Oral cholera vaccine (OCV) is safe and effective, but has not been seen as a primary tool for cholera elimination due to a limited period of protection and constrained supplies. Regionally, epidemic cholera is contained to the island of Hispaniola, and the lowest numbers of cases since the epidemic began were reported in 2019. Hence, Haiti may represent a unique opportunity to eliminate cholera with OCV. Methods: In this modelling study, we assessed the probability of elimination, time to elimination, and percentage of cases averted with OCV campaign scenarios in Haiti through simulations from four modelling teams. For a 10-year period from January 19, 2019, to Jan 13, 2029, we compared a no vaccination scenario with five OCV campaign scenarios that differed in geographical scope, coverage, and rollout duration. Teams used weekly department-level reports of suspected cholera cases from the Haiti Ministry of Public Health and Population to calibrate the models and used common vaccine-related assumptions, but other model features were determined independently. Findings: Among campaigns with the same vaccination coverage (70% fully vaccinated), the median probability of elimination after 5 years was 0–18% for no vaccination, 0–33% for 2-year campaigns focused in the two departments with the highest historical incidence, 0–72% for three-department campaigns, and 35–100% for nationwide campaigns. Two-department campaigns averted a median of 12–58% of infections, three-department campaigns averted 29–80% of infections, and national campaigns averted 58–95% of infections. Extending the national campaign to a 5-year rollout (compared to a 2-year rollout), reduced the probability of elimination to 0–95% and the proportion of cases averted to 37–86%. Interpretation: Models suggest that the probability of achieving zero transmission of Vibrio cholerae in Haiti with current methods of control is low, and that bolder action is needed to promote elimination of cholera from the region. Large-scale cholera vaccination campaigns in Haiti would offer the opportunity to synchronise nationwide immunity, providing near-term population protection while improvements to water and sanitation promote long-term cholera elimination. Funding: Bill & Melinda Gates Foundation, Global Good Fund, Institute for Disease Modeling, Swiss National Science Foundation, and US National Institutes of Health

Estudio de la organización genómica de elementos de ADN de Taxoplasma gondii y su aplicación al diagnóstico directo de la toxoplasmosis humana

Toxoplasma gondii es uno de los parásitos protozoarios más ampliamente distribuidos a nivel mundial, y usualmente causa una enfermedad asintomática en los humanos. Sin embargo, la reactivación de la infección crónica en pacientes inmunocomprometidos, y la toxoplasmosis congénita de una infección primaria adquirida durante el embarazo, presentan cuadros clínicos muy severos e incluso puede causar la muerte del paciente. Además, debido a que T. gondii causa mortalidad de los neonatos en ovejas, también representa una causa importante de pérdida económica en las granjas. En este trabajo dos familias de ADN repetitivas de T. gondii fueron caracterizadas. ABGTg7 (721 bp) presenta dos monómeros repetidos completos y 55 nt de un tercero, mostrando una disposición de tandems directos cuya unidad repetida es de aproximadamente 340 bp. ABGTg8 (1002 bp) contiene dos elementos repetidos distintos: uno denominado ABGTg8.2 y un elemento ABGTg7. ABGTg7 y ABGTg8.2 muestran patrones de hibridación muy similares en Southern-blots de ADN de T. gondii digerido con distintas endonucleasas de restricción, sugiriendo que ambos elementos principalmente se encuentran en la misma estructura repetitiva en tandem en el genoma. Análisis de PFGE mostraron que estos elementos repetidos se encuentran en al menos tres de los 4 cromosomas más grandes de T. gondii. Ensayos de sensibilidad a la endonucleasa Bal 31 indicaron que se encuentran localizados cerca de los telómeros de los cromosomas así como también en otras regiones de los mismos. Cinco fagos lambda recombinantes genómicos fueron aislados y dos clusters diferentes completos de la estructura repetitiva fueron analizados. Ambos clusters contienen uno de sus extremos conservados con un fragmento de 4.4 Kbp donde se halla ubicado ABGTg8.2, ligado a numerosos fragmentos Sal I conteniendo todos al menos una copia de los monómeros de ABGTg7. Dentro de estos clusters ambos elementos repetidos forman parte de una estructura compleja en tandem, donde los monómeros de ABGTg7 se encuentran dispuestos tanto como tandems directos como flanqueados por otros elementos repetitivos sin o con baja homología entre ellos. Esta estructura repetitiva en tandem cumple los requerimientos asignados al ADN satelital. Por otra parte, se evaluó el uso potencial de la secuencia ABGTg7 para el diagnóstico de la toxoplasmosis humana. Se realizaron ensayos de hibridación mediante la técnica de Dot-blot en muestras de sangre de pacientes con toxoplasmosis cerebral (CT), linfoadenopatía toxoplásmica (ATL) y toxoplasmosis diseminada en pacientes trasplantados (TR). Se estudió un total de 84 individuos. Se encontraron señales positivas por Dot-blot en 12 (66.7%) de 18 casos con CT confirmada, 9 (52.9%) de 17 casos con ATL y 2 (66.7%) de 3 casos con TR con toxoplasmosis. En paralelo se realizaron ensayos de PCR en los pacientes con ATL, resultando en la detección de ADN de T. gondii en 10 casos (58.8%). Un estudio comparativo entre el Dot-blot y la PCR fue realizado también en ratones experimentalmente infectados con taquizoitos, el cual arrojó resultados similares: 60% y 70% de valores positivos respectivamente. Finalmente la suma de valores positivos obtenidos con ambos tests (Dot-blot más PCR) incrementó el número de sospechas de infección toxoplásmica en los pacientes con ATL a un 76.4% de casos. Por otro lado, si se consideran los resultados positivos obtenidos simultáneamente por las dos técnicas, se confirmó el resultado en el 35.2% de los casos. Estos resultados indican que la sonda repetitiva ABGTg7 es un recurso adicional útil para el diagnóstico de la toxoplasmosis humana. Finalmente, teniendo en cuenta los resultados obtenidos en los estudios básicos sobre la organización genómica de estos elementos repetidos, se desarrolló un ensayo de PCR basado en la secuencia ABGTg7 con el objeto de ser evaluado como herramienta diagnóstica

Protection afforded by previous Vibrio cholerae infection against subsequent disease and infection: A review.

BackgroundCholera is an acute, diarrheal disease caused by Vibrio cholerae O1 or 139 that is associated with a high global burden.MethodsWe analyzed the estimated duration of immunity following cholera infection from available published studies. We searched PubMed and Web of Science for studies of the long-term immunity following cholera infection. We identified 22 eligible studies and categorized them as either observational, challenge, or serological.ResultsWe found strong evidence of protection at 3 years after infection in observational and challenge studies. However, serological studies show that elevated humoral markers of potential correlates of protection returned to baseline within 1 year. Additionally, a subclinical cholera infection may confer lower protection than a clinical one, as suggested by 3 studies that found that, albeit with small sample sizes, most participants with a subclinical infection from an initial challenge with cholera had a symptomatic infection when rechallenged with a homologous biotype.ConclusionsThis review underscores the need to elucidate potential differences in the protection provided by clinical and subclinical cholera infections. Further, more studies are warranted to bridge the gap between the correlates of protection and cholera immunity. Understanding the duration of natural immunity to cholera can help guide control strategies and policy

Vaccine optimization for COVID-19: Who to vaccinate first?

Vaccines, when available, will likely become our best tool to control the COVID-19 pandemic. Even in the most optimistic scenarios, vaccine shortages will likely occur. Using an age-stratified mathematical model paired with optimization algorithms, we determined optimal vaccine allocation for four different metrics (deaths, symptomatic infections, and maximum non-ICU and ICU hospitalizations) under many scenarios. We find that a vaccine with effectiveness ≥50% would be enough to substantially mitigate the ongoing pandemic, provided that a high percentage of the population is optimally vaccinated. When minimizing deaths, we find that for low vaccine effectiveness, irrespective of vaccination coverage, it is optimal to allocate vaccine to high-risk (older) age groups first. In contrast, for higher vaccine effectiveness, there is a switch to allocate vaccine to high-transmission (younger) age groups first for high vaccination coverage. While there are other societal and ethical considerations, this work can provide an evidence-based rationale for vaccine prioritization

One versus two doses: What is the best use of vaccine in an influenza pandemic?

Avian influenza A (H7N9), emerged in China in April 2013, sparking fears of a new, highly pathogenic, influenza pandemic. In addition, avian influenza A (H5N1) continues to circulate and remains a threat. Currently, influenza H7N9 vaccines are being tested to be stockpiled along with H5N1 vaccines. These vaccines require two doses, 21 days apart, for maximal protection. We developed a mathematical model to evaluate two possible strategies for allocating limited vaccine supplies: a one-dose strategy, where a larger number of people are vaccinated with a single dose, or a two-dose strategy, where half as many people are vaccinated with two doses. We prove that there is a threshold in the level of protection obtained after the first dose, below which vaccinating with two doses results in a lower illness attack rate than with the one-dose strategy; but above the threshold, the one-dose strategy would be better. For reactive vaccination, we show that the optimal use of vaccine depends on several parameters, with the most important one being the level of protection obtained after the first dose. We describe how these vaccine dosing strategies can be integrated into effective pandemic control plans

Optimal Vaccine Allocation for the Early Mitigation of Pandemic Influenza

<div><p>With new cases of avian influenza H5N1 (H5N1AV) arising frequently, the threat of a new influenza pandemic remains a challenge for public health. Several vaccines have been developed specifically targeting H5N1AV, but their production is limited and only a few million doses are readily available. Because there is an important time lag between the emergence of new pandemic strain and the development and distribution of a vaccine, shortage of vaccine is very likely at the beginning of a pandemic. We coupled a mathematical model with a genetic algorithm to optimally and dynamically distribute vaccine in a network of cities, connected by the airline transportation network. By minimizing the illness attack rate (i.e., the percentage of people in the population who become infected and ill), we focus on optimizing vaccine allocation in a network of 16 cities in Southeast Asia when only a few million doses are available. In our base case, we assume the vaccine is well-matched and vaccination occurs 5 to 10 days after the beginning of the epidemic. The effectiveness of all the vaccination strategies drops off as the timing is delayed or the vaccine is less well-matched. Under the best assumptions, optimal vaccination strategies substantially reduced the illness attack rate, with a maximal reduction in the attack rate of 85%. Furthermore, our results suggest that cooperative strategies where the resources are optimally distributed among the cities perform much better than the strategies where the vaccine is equally distributed among the network, yielding an illness attack rate 17% lower. We show that it is possible to significantly mitigate a more global epidemic with limited quantities of vaccine, provided that the vaccination campaign is extremely fast and it occurs within the first weeks of transmission.</p> </div

Population values.

a<p>The percentages for each city were computed from <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002964#pcbi.1002964-UN1" target="_blank">[58]</a> using the countr y's percentage of children under 20 years old. Taiwan's percentage was obtained from <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002964#pcbi.1002964-US1" target="_blank">[59]</a>.</p

Daily flux of passengers through the network.

<p>Percentage of the total number of daily passengers traveling through each city considered in the network.</p

Network representation of 16 cities in Southeast Asia used for the simulations.

<p>An edge connecting two cities represents daily travel between those cities. The size of the nodes in (A) correspond to the population size relative to the total population in the network. The size of the nodes in (B) correspond to the flux of passengers traveling through each city relative to the total number of flights in the network. The base case simulations were started in Jakarta, which accounts for 12.8% of the total population of the network but only 7% of the total daily travel goes through it.</p