The growing number of infectious disease outbreaks, like the one caused by the SARS-CoV-2 virus, underscores the necessity of actuarial models that can adapt to epidemic-driven risks. Traditional life insurance frameworks often rely on static mortality assumptions that fail to capture the temporal and behavioral complexity of disease transmission. In this paper, we propose an integrated actuarial framework based on the SEIARD epidemiological model. This framework enables the explicit modeling of incubation periods and disease-induced mortality. We derive key actuarial quantities, including the present value of annuity benefits, payment streams, and net premiums, based on SEIARD dynamics. We formulate a prospective reserve function and analyze its evolution throughout the course of an epidemic. Additionally, we examine the forces of infection, mortality, and removal to assess their impact on epidemic-adjusted survival probabilities. Numerical simulations implemented via a nonstandard finite difference (NSFD) scheme illustrate the model's applicability under various parameter settings and insurance policy assumptions.
Belinda Claire Kiam, Aline Gaelle Bouopda-Tuedom, Jean Arthur Mbida Mbida
et al.
Abstract Background Assessing vector bionomics and their role in transmission is crucial to improving vector control strategies. Several entomological studies have been conducted to describe malaria transmission in different eco-epidemiological settings in Cameroon; however, data gaps persist, particularly in the highland areas. This study aimed to characterize malaria vectors in three localities along an altitudinal gradient in the western region: Santchou (700 m), Dschang (1400 m) and Penka Michel (1500 m). Methods Human landing catches were conducted from May to June 2023 in 17 villages (including 10 health zones in Dschang, 4 in Santchou and 3 in Penka Michel) from 6:00 p.m. to 9:00 a.m. Mosquitoes were sorted into genera and all Anopheles species were identified using morphological taxonomic keys and species-specific Polymerase Chain reaction (PCR). Entomological indicators, including species composition, abundance, biting behaviour, infection rate and entomological inoculation rate (EIR) were assessed. Genomic DNA from the head and thorax was extracted and tested for Plasmodium infection by real-time PCR. Results A total of 2835 Anopheles mosquitoes were identified, including Anopheles gambiae sensu lato (s.l.) (82.88%), Anopheles funestus s.l. (15.92%), Anopheles nili (0.09%) and Anopheles ziemanni (1.11%), with An. gambiae s.l. being the most prevalent at all sites. Anopheles gambiae s.l. had a significantly higher human-biting rate at Penka Michel (45.25 bites/human/night) compared to Santchou (3.1 bites/human/night [b/h/n]) and Dschang (0.41 bites/human/night) (p-value < 0.001). It was also the main malaria vector, with an entomological inoculation rate (EIR) 13 times higher in Penka Michel than Santchou (1.11 vs. 0.08 infective bites/human/night). The data suggest a very focal distribution of infective An. gambiae s.l. mosquitoes. Plasmodium falciparum was the dominant malaria parasite (67% in Santchou, 62% in Penka Michel), but Plasmodium malariae (33% in Santchou, 31% in Penka Michel) and Plasmodium ovale (1.21% only in Penka Michel) infections were also detected. Conclusion The study highlights a difference in mosquito composition and host-seeking behaviour across altitudes, emphasizing the need for continued surveillance to monitor vector populations. To combat the persistence of malaria in Cameroon, it is crucial to implement additional tools like larviciding, integrated and environmental management, particularly against outdoor-biting mosquitoes, to prevent potential malaria outbreaks in these highland areas.
Arctic medicine. Tropical medicine, Infectious and parasitic diseases
A case of a patient who developed a radiation recall reaction (RRR) triggered by coronavirus disease 2019 (COVID-19) infection following surgery and chemoradiotherapy for carcinoma of the buccal mucosa is reported. A 75-year-old woman presented in October 2023 with pyrexia and erythema extending from the left cheek to the anterior chest area. In December 2021, she had undergone surgery to remove a carcinoma of the left buccal mucosa (pT2N0M0), followed by left comprehensive neck dissection for delayed cervical lymph node metastasis in June 2022, with subsequent adjuvant chemoradiotherapy. Her course was uneventful until September 2023, when she developed COVID-19. Twenty-three days after COVID-19 infection had been confirmed, she developed systemic pyrexia with erythema and a heat sensation from her left cheek to the left anterior chest. On presentation, her temperature was 39 ºC, and she had a mild sore throat. Erythema and a heat sensation were apparent from the left cheek to the neck and anterior chest, corresponding to the previously irradiated area. Laboratory tests showed a white blood cell count of 11,760/μl, and C-reactive protein of 16.0 mg/dl. Computed tomography did not show any obvious abscess formation or infection source. An RRR was diagnosed, and she was admitted for treatment with intravenous sulbactam/ampicillin and intravenous hydrocortisone sodium succinate. Five days after admission, the inflammatory reaction had improved, and she was discharged. Her subsequent course has been uneventful, with no flareup of the RRR. This case is presented along with a review of relevant literature.
Isolated primary tuberculoma of the paranasal sinuses is an exceedingly rare form of extra-pulmonary tuberculosis (EPTB), particularly in immunocompetent individuals. Its presentation is often atypical, mimicking aggressive neoplasms due to features such as local bone destruction, which complicates diagnosis and may lead to unnecessary invasive interventions. We report the case of a 32-year-old immunocompetent male presenting with chronic right nasal obstruction, rhinorrhoea, facial puffiness, hyposmia, and intermittent fever. Imaging revealed a heterogeneous mass in the right frontal, ethmoidal, and maxillary sinuses, with extensive bony erosion suggestive of a malignant etiology. Histopathological examination of biopsy tissue, however, demonstrated granulomatous inflammation with Langhans giant cells, necrosis, and acid-fast bacilli on Ziehl-Neelsen staining, confirming tuberculoma. Anti-tubercular treatment (ATT) was promptly initiated post-biopsy, leading to complete symptom resolution and no recurrence. This case sheds light on the importance of including tuberculoma in the differential diagnosis of aggressive sinonasal lesions in immunocompetent patients despite their rarity, and highlights the critical role of histopathology and ATT in effective management, potentially preventing extensive surgical resections and associated morbidity.
Laura Andrea Barrero Guevara, Sarah C Kramer, Tobias Kurth
et al.
A pressing question resulting from global warming is how infectious diseases will be affected by climate change. Answering this question requires research into the effects of weather on the population dynamics of transmission and infection; elucidating these effects, however, has proven difficult due to the challenges of assessing causality from the predominantly observational data available in epidemiological research. Here, we show how concepts from causal inference -- the sub-field of statistics aiming at inferring causality from data -- can guide that research. Through a series of case studies, we illustrate how such concepts can help assess study design and strategically choose a study's location, evaluate and reduce the risk of bias, and interpret the multifaceted effects of meteorological variables on transmission. More broadly, we argue that interdisciplinary approaches based on explicit causal frameworks are crucial for reliably estimating the effect of weather and accurately predicting the consequences of climate change.
Takako Yokota, Shuhei Kurosawa, Yukihiro Yoshimura
et al.
A 44-year-old HIV-positive man diagnosed with diffuse large B-cell lymphoma in 2021 achieved complete remission with six cycles of R-CHOP therapy but had a relapse in November 2022. ESHAP therapy failed to induce remission, leading to complete remission with four cycles of Pola-BR therapy. Post-failure of autologous stem cell harvest, cord blood transplantation (CBT) was performed in June 2023. Notably, this case used recently approved intramuscular antiretroviral therapy (ART) with cabotegravir and rilpivirine, addressing gastrointestinal complications during CBT. This innovative use of intramuscular ART in the treatment of malignancy represents a first in the field, offering a pioneering approach to HIV-related lymphoma.
Monitoring key elements of disease dynamics (e.g., prevalence, case counts) is of great importance in infectious disease prevention and control, as emphasized during the COVID-19 pandemic. To facilitate this effort, we propose a new capture-recapture (CRC) analysis strategy that takes misclassification into account from easily-administered, imperfect diagnostic test kits, such as the Rapid Antigen Test-kits or saliva tests. Our method is based on a recently proposed "anchor stream" design, whereby an existing voluntary surveillance data stream is augmented by a smaller and judiciously drawn random sample. It incorporates manufacturer-specified sensitivity and specificity parameters to account for imperfect diagnostic results in one or both data streams. For inference to accompany case count estimation, we improve upon traditional Wald-type confidence intervals by developing an adapted Bayesian credible interval for the CRC estimator that yields favorable frequentist coverage properties. When feasible, the proposed design and analytic strategy provides a more efficient solution than traditional CRC methods or random sampling-based biased-corrected estimation to monitor disease prevalence while accounting for misclassification. We demonstrate the benefits of this approach through simulation studies that underscore its potential utility in practice for economical disease monitoring among a registered closed population.
Aaron Gerding, Nicholas G. Reich, Benjamin Rogers
et al.
Recent years have seen increasing efforts to forecast infectious disease burdens, with a primary goal being to help public health workers make informed policy decisions. However, there has only been limited discussion of how predominant forecast evaluation metrics might indicate the success of policies based in part on those forecasts. We explore one possible tether between forecasts and policy: the allocation of limited medical resources so as to minimize unmet need. We use probabilistic forecasts of disease burden in each of several regions to determine optimal resource allocations, and then we score forecasts according to how much unmet need their associated allocations would have allowed. We illustrate with forecasts of COVID-19 hospitalizations in the US, and we find that the forecast skill ranking given by this allocation scoring rule can vary substantially from the ranking given by the weighted interval score. We see this as evidence that the allocation scoring rule detects forecast value that is missed by traditional accuracy measures and that the general strategy of designing scoring rules that are directly linked to policy performance is a promising direction for epidemic forecast evaluation.
With the covid-19 pandemic still ongoing and an enormous amount of test data available, the lessons learned over the last two years need to be developed to a point where they can provide understanding for tackling new variants and future diseases. The SIR-model commonly used to model disease spread, predicts exponential initial growth, which helps establish the infectiousness of a disease in the early days of an outbreak. Unfortunately, the exponential growth becomes muddied by spatial, finite-size, and non-equilibrium effects in realistic systems, and robust estimates that may be used in prediction and description are still lacking. I here establish a second quantization framework that allows introduction of arbitrarily complicated spatial behavior, and I show that a simplified version of this model is in good agreement with both the growth of different covid-19 variants in Denmark and analytical results from the theory of branched polymers. Denmark is well-suited for comparison, because the number of tests with variant information in early December 2021 is very high, so the spread of a single variant can be followed. I expect this model to build bridges between the epidemic modeling and solid state communities. The long-term goal of the particular analysis in this paper is to establish priors that allow better early estimates for the infectiousness of a new disease.
Abstract Background We aimed to clarify the characteristics, risk factors, and prognosis of stroke among HAART-naive people living with HIV (PLWH) in China. Methods We selected HAART-naive PLWH admitted to Beijing Ditan Hospital, Capital Medical University, from 1 January 2009 to 31 December 2019. Demographic and clinical data were obtained by searching an anonymous electronic case system. Descriptive analysis and logistic regression and Cox proportional hazard models were used to determine the characteristics and predictors of stroke among all HAART-naive PLWH and evaluate the risk factors of mortality in HAART-naive PLWH with stroke. Results Stroke was diagnosed in 105 cases (3.7%) of 2867 HAART-naive PLWH. Multivariate logistic regression indicated that age of 30–55 years (OR 1.903, 95% CI 1.005–3.603, p = 0.048), age of ≥ 55 years (OR 4.104, 95% CI 1.928–8.737, p < 0.001), and CD4 count of < 200 cells/µL (OR 2.005, 95% CI 1.008–3.985, p = 0.047) were associated with increased odds of stroke. Diabetes (OR 3.268, 95% CI 1.744–6.125, p < 0.001), hypertension (OR 2.301, 95% CI 1.425–3.717, p = 0.001), syphilis (OR 2.003, 95% CI 1.300–3.089, p = 0.002), and complicated AIDS-defining CNS diseases (OR 7.719, 95% CI 4.348–13.703, p < 0.001) were risk factors for stroke. Of the 105 stroke patients, 12 (11.4%) died during hospitalisation, and the risk factors for mortality among patients with stroke were age of > 65 years (AHR: 8.783, 95% CI 1.522–50.668, p = 0.015), complicated severe pneumonia (AHR: 3.940, 95% CI 1.106–14.029, p = 0.034), and AIDS-defining CNS diseases (AHR: 19.766, 95% CI 3.586–108.961, p = 0.001). Conclusions For HAART-naive people living with HIV (PLWH), stroke occurred in various age groups, and early screening for stroke, timely intervention for risk factors among patients in various age groups, and controlling the CD4 count are extremely important in reducing the burden of stroke.
Gavin Yamey, Kaci Kennedy McDade, Wenhui Mao
et al.
Background Although it is difficult to quantify, previous estimates suggested that China’s global health aid has increased sharply since the early 2000s. Unlike many donors, China has no official aid reporting obligations, nor does it voluntarily disclose detailed aid information. Our study aimed to create a standardised estimate using commonly accepted definitions of aid and frameworks for categorising health projects.Methods We categorised AidData’s Chinese Official Finance Dataset health-related projects according to health aid frameworks from the Organisation for Economic Co-operation and Development (OECD) and the Institute for Health Metrics and Evaluation (IHME). Only projects that complied with the definition of official development assistance were included. We analysed the project count and financial value to assess China’s priority health aid areas.Findings Between 2000 and 2017, China funded 1339 health-related aid projects, or 13% of its total aid project portfolio. Most of these projects were located in sub-Saharan Africa. According to the OECD framework, the priority focus areas of these projects were: medical services, such as specialty equipment and tertiary services (n=489, 37%); basic health care, such as basic medical services and drugs (n=251, 19%); malaria control (n=234, 18%) and basic health infrastructure (n=178, 13%). Under the IHME framework, health systems strengthening accounted for 74% (n=991) of total projects, primarily due to China’s contributions to human resources for health, infrastructure and equipment. The only other major allocation under the IHME framework was malaria (n=234, 18%). When we estimated missing financial values under the OECD framework, China was the fifth largest health aid donor to African countries from 2002 to 2017, after the USA, the UK, Canada and Germany.Conclusion Our findings enable a better understanding of Chinese health aid in the absence of transparent aid reporting, which could contribute to better coordination, collaboration and resource allocation for both donor and recipient countries.
Medicine (General), Infectious and parasitic diseases
Gill disease of farmed Atlantic salmon (Salmo salar) in the marine environment has emerged as a significant problem for the salmon aquaculture industry. Different types of marine salmon gill disease reported include amoebic gill disease (AGD), parasitic gill disease, viral gill disease, bacterial gill disease, zooplankton (cnidarian nematocyst)-associated gill disease, harmful algal gill disease and chemical/toxin-associated gill disease. The term ‘multifactorial gill disease’ is used when multiple distinguishable types of disease (as opposed to an obvious single primary type) are present. When gill disease is non-specific, it is referred to as ‘complex gill disease’ (CGD) or ‘complex gill disorder’. These two terms are often used interchangeably and are overlapping. The significance of many infectious and non-infectious agents that may be associated with CGD is often unclear. In this review, we summarise aspects of the different types of gill disease that are relevant to the epidemiology of gill disease and of CGD in particular. We also tabulate simultaneously occurring putative pathogens to explore the multifactorial nature of gill disease.
IntroductionIntestinal parasites are among the most prevalent foodborne diseases worldwide, and raw vegetables and herbs are among the primary sources of human infection by these parasites. This study aimed to investigate the prevalence of parasitic contamination of fresh herbs in Shushtar, Khuzestan Province, Southwest of Iran.MethodsIn this study, 129 herb samples from various farms were collected and washed with water. The washing waters were centrifuged, and the resulting sediments were examined by formol-ether concentration and Sheatherchr('39')s sugar flotation procedure, as well as a wet smear and Ziehl-Neelsen staining.ResultsAmong the 129 samples, 73.6% (n=95) showed contamination with at least one parasite, including trophozoite like amoebae (52.6%), followed by Giardia lamblia (14.7%), Cryptosporidium spp. (2.1%), Blastocystis sp. (21%), free-living nematodes larvae (3.1%), Trichostrongilid nematodes (1.05%), Ascaris lumericoids eggs (2.1%), Hymenolepis spp. (2.1%) and Taeniid eggs (1.05%).ConclusionA high prevalence rate of parasitic contaminations of herbs in Shushtar necessitates proper washing of herbs and vegetables by consumers to prevent parasitic infections.
This article introduces epidemia, an R package for Bayesian, regression-oriented modeling of infectious diseases. The implemented models define a likelihood for all observed data while also explicitly modeling transmission dynamics: an approach often termed as semi-mechanistic. Infections are propagated over time using renewal equations. This approach is inspired by self-exciting, continuous-time point processes such as the Hawkes process. A variety of inferential tasks can be performed using the package. Key epidemiological quantities, including reproduction numbers and latent infections, may be estimated within the framework. The models may be used to evaluate the determinants of changes in transmission rates, including the effects of control measures. Epidemic dynamics may be simulated either from a fitted model or a prior model; allowing for prior/posterior predictive checks, experimentation, and forecasting.
We study a model for the spread of an infectious disease which incorporates spatial and temporal effects. The model is a delayed multi-type branching process in which types represent geographic regions while infected individuals reproduce offspring during a finite time interval and have convalescence times and random death/recovery outcomes. We give simple expressions for the limit of the geometrically weighted mean evolution of the process.
Xiaoxiao Li, Matthew Ferrari, Michael J. Tildesley
et al.
Motivated by foot-and-mouth disease (FMD) outbreak data from Turkey, we develop a model to estimate disease risk based on a space-time record of outbreaks. The spread of infectious disease in geographical units depends on both transmission between neighbouring units and the intrinsic susceptibility of each unit to an outbreak. Spatially correlated susceptibility may arise from known factors, such as population density, or unknown (or unmeasured) factors such as commuter flows, environmental conditions, or health disparities. Our framework accounts for both space-time transmission and susceptibility. We model the unknown spatially correlated susceptibility as a Gaussian process. We show that the susceptibility surface can be estimated from observed, geo-located time series of infection events and use a projection-based dimension reduction approach which improves computational efficiency. In addition to identifying high risk regions from the Turkey FMD data, we also study how our approach works on the well known England-Wales measles outbreaks data; our latter study results in an estimated susceptibility surface that is strongly correlated with population size, consistent with prior analyses.