Nowcasting and forecasting COVID-19 waves: the recursive and stochastic nature of transmission.

We propose a parsimonious, yet effective, susceptible-exposed-infected-removed-type model that incorporates the time change in the transmission and death rates. The model is calibrated by Tikhonov-type regularization from official reports from New York City (NYC), Chicago, the State of São Paulo, in Brazil and British Columbia, in Canada. To forecast, we propose different ways to extend the transmission parameter, considering its estimated values. The forecast accuracy is then evaluated using real data from the above referred places. All the techniques accurately provided forecast scenarios for periods 15 days long. One of the models effectively predicted the magnitude of the four waves of infections in NYC, including the one caused by the Omicron variant for periods of 45 days using out-of-sample data.

Estimating the number of unvaccinated Chinese workers against yellow fever in Angola.

BACKGROUND: A yellow fever epidemic occurred in Angola in 2016 with 884 laboratory confirmed cases and 373 deaths. Eleven unvaccinated Chinese nationals working in Angola were also infected and imported the disease to China, thereby presenting the first importation of yellow fever into Asia. In Angola, there are about 259,000 Chinese foreign workers. The fact that 11 unvaccinated Chinese workers acquired yellow fever suggests that many more Chinese workers in Angola were not vaccinated. METHODS: We applied a previously developed model to back-calculate the number of unvaccinated Chinese workers in Angola in order to determine the extent of lack of vaccine coverage. RESULTS: Our models suggest that none of the 259,000 Chinese had been vaccinated, although yellow fever vaccination is mandated by the International Health Regulations. CONCLUSION: Governments around the world including China need to ensure that their citizens obtain YF vaccination when traveling to countries where such vaccines are required in order to prevent the international spread of yellow fever.

ZikaPLAN: Zika Preparedness Latin American Network.

The ongoing Zika virus (ZIKV) outbreak in Latin America, the Caribbean, and the Pacific Islands has underlined the need for a coordinated research network across the whole region that can respond rapidly to address the current knowledge gaps in Zika and enhance research preparedness beyond Zika. The European Union under its Horizon 2020 Research and Innovation Programme awarded three research consortia to respond to this need. Here we present the ZikaPLAN (Zika Preparedness Latin American Network) consortium. ZikaPLAN combines the strengths of 25 partners in Latin America, North America, Africa, Asia, and various centers in Europe. We will conduct clinical studies to estimate the risk and further define the full spectrum and risk factors of congenital Zika virus syndrome (including neurodevelopmental milestones in the first 3 years of life), delineate neurological complications associated with ZIKV due to direct neuroinvasion and immune-mediated responses in older children and adults, and strengthen surveillance for birth defects and Guillain-Barré Syndrome. Laboratory-based research to unravel neurotropism and investigate the role of sexual transmission, determinants of severe disease, and viral fitness will underpin the clinical studies. Social messaging and engagement with affected communities, as well as development of wearable repellent technologies against Aedes mosquitoes will enhance the impact. Burden of disease studies, data-driven vector control, and vaccine modeling as well as risk assessments on geographic spread of ZIKV will form the foundation for evidence-informed policies. While addressing the research gaps around ZIKV, we will engage in capacity building in laboratory and clinical research, collaborate with existing and new networks to share knowledge, and work with international organizations to tackle regulatory and other bottlenecks and refine research priorities. In this way, we can leverage the ZIKV response toward building a long-term emerging infectious diseases response capacity in the region to address future challenges.

On the origin and timing of Zika virus introduction in Brazil.

The timing and origin of Zika virus (ZIKV) introduction in Brazil has been the subject of controversy. Initially, it was assumed that the virus was introduced during the FIFA World Cup in June-July 2014. Then, it was speculated that ZIKV may have been introduced by athletes from French Polynesia (FP) who competed in a canoe race in Rio de Janeiro in August 2014. We attempted to apply mathematical models to determine the most likely time window of ZIKV introduction in Brazil. Given that the timing and origin of ZIKV introduction in Brazil may be a politically sensitive issue, its determination (or the provision of a plausible hypothesis) may help to prevent undeserved blame. We used a simple mathematical model to estimate the force of infection and the corresponding individual probability of being infected with ZIKV in FP. Taking into account the air travel volume from FP to Brazil between October 2013 and March 2014, we estimated the expected number of infected travellers arriving at Brazilian airports during that period. During the period between December 2013 and February 2014, 51 individuals travelled from FP airports to 11 Brazilian cities. Basing on the calculated force of ZIKV infection (the per capita rate of new infections per time unit) and risk of infection (probability of at least one new infection), we estimated that 18 (95% CI 12-22) individuals who arrived in seven of the evaluated cities were infected. When basic ZIKV reproduction numbers greater than one were assumed in the seven evaluated cities, ZIKV could have been introduced in any one of the cities. Based on the force of infection in FP, basic reproduction ZIKV number in selected Brazilian cities, and estimated travel volume, we concluded that ZIKV was most likely introduced and established in Brazil by infected travellers arriving from FP in the period between October 2013 and March 2014, which was prior to the two aforementioned sporting events.

Magnitude and frequency variations of vector-borne infection outbreaks using the Ross-Macdonald model: explaining and predicting outbreaks of dengue fever.

The classical Ross-Macdonald model is often utilized to model vector-borne infections; however, this model fails on several fronts. First, using measured (or estimated) parameters, which values are accepted from the literature, the model predicts a much greater number of cases than what is usually observed. Second, the model predicts a single large outbreak that is followed by decades of much smaller outbreaks, which is not consistent with what is observed. Usually towns or cities report a number of recurrences for many years, even when environmental changes cannot explain the disappearance of the infection between the peaks. In this paper, we continue to examine the pitfalls in modelling this class of infections, and explain that, if properly used, the Ross-Macdonald model works and can be used to understand the patterns of epidemics and even, to some extent, be used to make predictions. We model several outbreaks of dengue fever and show that the variable pattern of yearly recurrence (or its absence) can be understood and explained by a simple Ross-Macdonald model modified to take into account human movement across a range of neighbourhoods within a city. In addition, we analyse the effect of seasonal variations in the parameters that determine the number, longevity and biting behaviour of mosquitoes. Based on the size of the first outbreak, we show that it is possible to estimate the proportion of the remaining susceptible individuals and to predict the likelihood and magnitude of the eventual subsequent outbreaks. This approach is described based on actual dengue outbreaks with different recurrence patterns from some Brazilian regions.

Interpretations and pitfalls in modelling vector-transmitted infections.

In this paper we propose a debate on the role of mathematical models in evaluating control strategies for vector-borne infections. Mathematical models must have their complexity adjusted to their goals, and we have basically two classes of models. At one extreme we have models that are intended to check if our intuition about why a certain phenomenon occurs is correct. At the other extreme, we have models whose goals are to predict future outcomes. These models are necessarily very complex. There are models in between these classes. Here we examine two models, one of each class and study the possible pitfalls that may be incurred. We begin by showing how to simplify the description of a complicated model for a vector-borne infection. Next, we examine one example found in a recent paper that illustrates the dangers of basing control strategies on models without considering their limitations. The model in this paper is of the second class. Following this, we review an interesting paper (a model of the first class) that contains some biological assumptions that are inappropriate for dengue but may apply to other vector-borne infections. In conclusion, we list some misgivings about modelling presented in this paper for debate.

Will people change their vector-control practices in the presence of an imperfect dengue vaccine?

Human behaviours, which are influenced by social, cultural, economic and political factors, can increase or decrease the risk of dengue infection, depending on the relationship with the insect vector. Because no vaccine is currently available, the spread of dengue can only be curtailed by controlling vector populations (Aedes aegypti and others) and by protecting individuals. This study tested the hypothesis that dengue-affected populations are likely to relax their vector-control habits if a potentially protective vaccine becomes available. The hypothesis was tested using two approaches: a mathematical model designed to describe dengue transmission and an empirical field test in which the local population of an endemic area was interviewed about their vector-control habits given the presence of a theoretical vaccine. The model demonstrated that depending on the level of vector-control reduction, there is a threshold in vaccine efficacy below which it is better not to introduce the vaccine. The interview showed that people who were informed that a very effective vaccine is available would reduce their vector-control habits significantly compared to a group that was informed that the vaccine is not very effective.

Dengue infections in non-immune travellers to Thailand.

Dengue is the most frequent arboviral disease and is expanding geographically. Dengue is also increasingly being reported in travellers, in particular in travellers to Thailand. However, data to quantify the risk of travellers acquiring dengue when travelling to Thailand are lacking. Using mathematical modelling, we set out to estimate the risk of non-immune persons acquiring dengue when travelling to Thailand. The model is deterministic with stochastic parameters and assumes a Poisson distribution for the mosquitoes' biting rate and a Gamma distribution for the probability of acquiring dengue from an infected mosquito. From the force of infection we calculated the risk of dengue acquisition for travellers to Thailand arriving in a typical year (averaged over a 17-year period) in the high season of transmission. A traveller arriving in the high season of transmission and remaining for 7 days has a risk of acquiring dengue of 0·2% (95% CI 0·16-0·23), whereas the risk for travel of 15 and 30 days' duration is 0·46% (95% CI 0·41-0·50) and 0·81% (95% CI 0·76-0·87), respectively. Our data highlight that the risk of non-immune travellers acquiring dengue in Thailand is substantial. The incidence of 0·81% after a 1-month stay is similar to that reported in prospective seroconversion studies in Israeli travellers to Thailand, highlighting that our models are consistent with actual data. Risk estimates based on mathematical modelling offer more detailed information depending on various travel scenarios, and will help the travel medicine provider give better evidence-based advice for travellers to dengue-endemic countries.

Does anti-hepatitis B virus vaccine make any difference in long-term number of liver transplantation?

BACKGROUND: Hepatitis B virus (HBV) infection is a major cause of morbidity and mortality worldwide. Chronic hepatitis B infection is associated with an increased risk of cirrhosis, hepatic decompensation, and hepatocellular carcinoma. Our aim is to analyze, through a mathematical model, the potential impact of anti-HBV vaccine in the long-term (that is, decades after vaccination) number of LT. METHODS: The model simulated that the prevalence of HBV infection was 0.5% and that approximately 20% of all the liver transplantation carried out in the state of São Paulo are due to HBV infection. RESULTS: The theoretical model suggests that a vaccination program that would cover 80% of the target population would reach a maximum of about 14% reduction in the LT program. CONCLUSION: Increasing the vaccination coverage against HBV in the state of São Paulo would have a relatively low impact on the number of liver transplantation. In addition, this impact would take several decades to materialize due to the long incubation period of liver failure due to HBV.

Estimation of R0 from the initial phase of an outbreak of a vector-borne infection.

The magnitude of the basic reproduction ratio R(0) of an epidemic can be estimated in several ways, namely, from the final size of the epidemic, from the average age at first infection, or from the initial growth phase of the outbreak. In this paper, we discuss this last method for estimating R(0) for vector-borne infections. Implicit in these models is the assumption that there is an exponential phase of the outbreaks, which implies that in all cases R(0)>1. We demonstrate that an outbreak is possible, even in cases where R(0) is less than one, provided that the vector-to-human component of R(0) is greater than one and that a certain number of infected vectors are introduced into the affected population. This theory is applied to two real epidemiological dengue situations in the southeastern part of Brazil, one where R(0) is less than one, and other one where R(0) is greater than one. In both cases, the model mirrors the real situations with reasonable accuracy.

A hypothesis for the 2007 dengue outbreak in Singapore.

A previous mathematical model explaining dengue in Singapore predicted a reasonable outbreak of about 6500 cases for 2006 and a very mild outbreak with about 2000 cases for 2007. However, only 3051 cases were reported in 2006 while more than 7800 were reported in the first 44 weeks of 2007. We hypothesized that the combination of haze with other local sources of particulate matter had a significant impact on mosquito life expectancy, significantly increasing their mortality rate. To test the hypothesis a mathematical model based on the reproduction number of dengue fever and aimed at comparing the impact of several possible alternative control strategies was proposed. This model also aimed at contributing to the understanding of the causes of dengue resurgence in Singapore in the last decade. The model's simulation demonstrated that an increase in mosquito mortality in 2006 and either a reduction in mortality or an increase in the carrying capacity of mosquitoes in 2007 explained the patterned observed in Singapore. Based on the model's simulation we concluded that the fewer than expected number of dengue cases in Singapore in 2006 was caused by an increase in mosquito mortality due to the disproportionate haze affecting the country that year and that particularly favourable environmental conditions in 2007 propitiated mosquitoes with a lower mortality rate, which explains the greater than expected number of dengue cases in 2007. Whether our hypothesis is plausible or not should be debated further.

Potential effect of using ABO-compatible living-donor liver transplantation.

Liver transplantation increased 1.84-fold from 1988 to 2004. However, the number of patients on the waiting list for a liver increased 2.71-fold, from 553 to 1500. We used a mathematical equation to analyze the potential effect of using ABO-compatible living-donor liver transplantation (LDLT) on both our liver transplantation program and the waiting list. We calculated the prevalence distribution of blood groups (O, A, B, and AB) in the population and the probability of having a compatible parent or sibling for LDLT. The incidence of ABO compatibility in the overall population was as follows: A, 0.31; B, 0.133; O, 0.512; and AB, 0.04. The ABO compatibility for parent donors was blood group A, 0.174; B, 0.06; O, 0.152; and AB, 0.03; and for sibling donors was A, 0.121; B, 0.05; O, 0.354; and AB, 0.03. Use of LDLT can reduce the pressure on our liver transplantation waiting list by decreasing its size by at least 16.5% at 20 years after its introduction. Such a program could save an estimated 3600 lives over the same period.

Seroepidemiology of Toxoplasma infection in a metropolitan region of Brazil.

Seroprevalence data from a representative population were used to estimate the annual incidence of congenital toxoplasmosis in São Paulo Metropolitan Region (SPMR). Retrospective anti-toxoplasma IgG serological analysis was conducted to determine age-dependent seroprevalence, force of infection, average age of acquisition of infection and curve of decay of maternally derived antibodies. Seroprevalence was used to calculate the number of new infections. Toxoplasmosis in pregnant women was estimated by total number of deliveries in a given year as a proxy for the number of pregnancies per year. Toxoplasma seroprevalence was 64.9% in women of childbearing age. Average age of acquisition of toxoplasmosis was 10.74 years. The estimated annual incidence of congenital toxoplasmosis varied from 9.5 to 10.6/1000 births in the studied period. The toxoplasmosis seroprevalence model allowed a good incidence estimation of congenital disease in SPMR compared to other published data, indicating that this mathematical approach is useful in calculating the potential demand of congenital disease due to Toxoplasma gondii in a given community.

Spatio-Temporal Tracking and Phylodynamics of an Urban Dengue 3 Outbreak in São Paulo, Brazil

The dengue virus has a single-stranded positive-sense RNA genome of ,10.700 nucleotides with a single open readingframe that encodes three structural (C, prM, and E) and seven nonstructural (NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5)proteins. It possesses four antigenically distinct serotypes (DENV 1–4). Many phylogenetic studies address particularities ofthe different serotypes using convenience samples that are not conducive to a spatio-temporal analysis in a single urbansetting. We describe the pattern of spread of distinct lineages of DENV-3 circulating in Sa˜o Jose´ do Rio Preto, Brazil, during2006. Blood samples from patients presenting dengue-like symptoms were collected for DENV testing. We performed M-NPCRusing primers based on NS5 for virus detection and identification. The fragments were purified from PCR mixtures andsequenced. The positive dengue cases were geo-coded. To type the sequenced samples, 52 reference sequences werealigned. The dataset generated was used for iterative phylogenetic reconstruction with the maximum likelihood criterion.The best demographic model, the rate of growth, rate of evolutionary change, and Time to Most Recent Common Ancestor(TMRCA) were estimated...

A hypothesis for explaining single outbreaks (like the Black Death in European cities) of vector-borne infections.

We propose a mechanism by which single outbreaks of vector-borne infections can happen even when the value of the basic reproduction number, R(0), of the infection is below one. With this hypothesis we have shown that dynamical models simulations demonstrate that the arrival of a relatively small (with respect to the host population) number of infected vectors can trigger a short-lived epidemic but with a huge number of cases. These episodes are characterized by a sudden outbreak in a previously virgin area that last from weeks to a few months, and then disappear without leaving vestiges. The hypothesis proposed in this paper to explain those single outbreaks of vector-borne infections, even when total basic reproduction number, R(0), is less than one (which explain the fact that those infections fail to establish themselves at endemic levels), is that the vector-to-host component of R(0) is greater than one and that a sufficient amount of infected vectors are imported to the vulnerable area, triggering the outbreak. We tested the hypothesis by performing numerical simulations that reproduce the observed outbreaks of chikungunya in Italy in 2007 and the plague in Florence in 1348. The theory proposed provides an explanation for isolated outbreaks of vector-borne infections, ways to calculate the size of those outbreaks from the number of infected vectors arriving in the affected areas. Given the ever-increasing worldwide transportation network, providing a high degree of mobility from endemic to virgin areas, the proposed mechanism may have important implications for public health planning.

Cost-effectiveness analysis of a hypothetical hepatitis C vaccine compared to antiviral therapy.

We propose a mathematical model to simulate the dynamics of hepatitis C virus (HCV) infection in the state of São Paulo, Brazil. We assumed that a hypothetical vaccine, which cost was taken to be the initial cost of the vaccine against hepatitis B exists and it is introduced in the model. We computed its cost-effectiveness compared with the anti-HCV therapy. The calculated basic reproduction number was 1.20. The model predicts that without intervention a steady state exists with an HCV prevalence of 3%, in agreement with the current epidemiological data. Starting from this steady state three interventions were simulated: indiscriminate vaccination, selective vaccination and anti-HCV therapy. Selective vaccination proved to be the strategy with the best cost-effectiveness ratio, followed by indiscriminate vaccination and anti-HCV therapy.

Vaccinating the vampire bat Desmodus rotundus against rabies.

The objective of this study was to extend the previous work of indirect oral rabies immunization of vampire bats (Desmodus rotundus) maintained in captivity, which demonstrated the immunogenicity of the V-RG vaccine (Vaccinia-Rabies Glycoprotein) and indicated that although the results had been encouraging, a new method for concentrating the vaccine should be tested in order to avoid vaccine loss and increase the survival proportion of bats after rabies challenge. In this study, three groups of seven bats each were tested with vaccine concentrated by ultrafiltration through a cellulose membrane. The vaccine was homogenized in Vaseline paste and applied to the back of one vector bat, which was then reintroduced into its group. A dose of 10(5.0) MICLD(50) rabies virus was used by intramuscular route to challenge the bats postvaccination. The survival proportion in the three groups after the challenge was 71.4%, 71.4% and 100%.