Malaria remains a major health challenge in developing countries, with climate change intensifying its impact. Pakistan is among the most vulnerable nations. This study examines the relationship between temperature and malaria cases in two highly affected districts, Bannu and Lakki Marwat, to inform climate-adaptive interventions.

We analyzed monthly malaria cases (2014–2022) from the Integrated Vector Control/Malaria Control Program in Khyber Pakhtunkhwa, combined with gridded meteorological data from Copernicus ERA5-Land. Time-series analysis using distributed lag nonlinear models and quasi-Poisson regression was applied to assess the associations.

The findings suggest that as temperatures exceed 22.4°C, malaria transmission increases by 9 to 10% for every 1°C rise in both districts. In Bannu, up to 39.8% of reported malaria cases could be attributed to heat, while in Lakki Marwat, 54.1% of cases were attributable to heat. Under high emission scenarios, heat-related malaria cases could increase by 0.8 to 3.5% by the 2060s. Relationship between temperature and malaria transmission is complex and is influenced by environmental factors such as precipitation and humidity.

Given Pakistan’s limited healthcare infrastructure, addressing climate-driven malaria risks is urgent. Recent severe floods and malaria surges highlight the need for climate adaptation measures and strengthened healthcare systems to enhance community resilience.

We introduce and study a game-theoretic model to understand the spread of an epidemic in a homogeneous population. A discrete-time stochastic process is considered where, in each epoch, first, a randomly chosen agent updates their action trying to maximize a proposed utility function, and then agents who have viral exposures beyond their immunity get infected. Our main results discuss asymptotic limiting distributions of both the cardinality of the subset of infected agents and the action profile, considered under various values of two parameters (initial action and immunity profile). We also show that the theoretical distributions are almost always achieved in the first few epochs.

The study of many population growth models is complicated by only partial observation of the underlying stochastic process driving the model. For example, in an epidemic outbreak we might know when individuals show symptoms to a disease and are removed, but not when individuals are infected. Motivated by the above example and the long-established approximation of epidemic processes by branching processes, we explore the number of individuals alive in a time-inhomogeneous branching process with a general phase-type lifetime distribution given only (partial) information on the times of deaths of individuals. Deaths are detected independently with a detection probability that can vary with time and type. We show that the number of individuals alive immediately after the kth detected death can be expressed as the mixture of random variables each of which consists of the sum of k independent zero-modified geometric distributions. Furthermore, in the case of an Erlang lifetime distribution, we derive an easy-to-compute mixture of negative binomial distributions as an approximation of the number of individuals alive immediately after the kth detected death.

Current standard microbiological techniques are generally very time consuming, usually requiring 24–72 h to establish a diagnosis. Consequentially, contemporary clinical practices implement broad-spectrum antibiotic administration prior to pathogen detection, prompting the emergence of extremely dangerous antibiotic-resistant bacteria. Additionally, lengthy test-to-result turnover times can greatly exacerbate the rate of disease spread. Rapid point-of-care (POC) diagnostics has quickly gained importance since the SARS-CoV-2 pandemic; accordingly, we have developed a rapid four-channel POC plasmonic quantitative polymerase chain reaction (qPCR) machine (Kimera P-IV) to respond to the deficiencies in infection control. Utilizing gold nanorods (GNRs) as nano-heaters and integrating vertical cavity surface emitting lasers (VCSEL) to replace traditional Peltier blocks, the Kimera P-IV has also incorporated quantitative real-time fluorescent monitoring. Using Chlamydia trachomatis genetic material to evaluate the rapid thermocycling performance of the platform, we have generated positive amplicons in less than 13 min; however, to achieve these results, several biological reagent considerations needed to be taken into account, specifically primer design. The device can achieve a limit of detection (LoD) of <101 DNA copies, a PCR efficiency of 88.3%, and can differentiate positive from negative results with 100% accuracy. Moreover, it can also analyze C. trachomatis DNA spiked urine samples via a simple dilution, suggesting that a separate nucleic acid step may not be needed for diagnosing infections. In conclusion, the operation of the Kimera P-IV prototype places it in a unique position of POC devices to revolutionize infectious disease diagnosis.

In this paper, we provide a systematic review of existing artificial intelligence (AI) regulations in Europe, the United States, and Canada. We build on the qualitative analysis of 129 AI regulations (enacted and not enacted) to identify patterns in regulatory strategies and in AI transparency requirements. Based on the analysis of this sample, we suggest that there are three main regulatory strategies for AI: AI-focused overhauls of existing regulation, the introduction of novel AI regulation, and the omnibus approach. We argue that although these types emerge as distinct strategies, their boundaries are porous as the AI regulation landscape is rapidly evolving. We find that across our sample, AI transparency is effectively treated as a central mechanism for meaningful mitigation of potential AI harms. We therefore focus on AI transparency mandates in our analysis and identify six AI transparency patterns: human in the loop, assessments, audits, disclosures, inventories, and red teaming. We contend that this qualitative analysis of AI regulations and AI transparency patterns provides a much needed bridge between the policy discourse on AI, which is all too often bound up in very detailed legal discussions and applied sociotechnical research on AI fairness, accountability, and transparency.

Cellulitis, a common subcutaneous infection, is influenced by host, pathogen, and environmental factors. Previous studies have shown seasonal patterns in adult cellulitis, suggesting temperature as a risk factor. This study investigated seasonal patterns in paediatric cellulitis in Jerusalem’s semi-arid climate. A single-center retrospective cohort study reviewed medical records of 2,219 hospitalized children under 18 with cellulitis between 1990 and 2020. Demographic, clinical, temperature, and humidity data were collected. Results revealed a significant sinusoidal pattern for limb cellulitis (LC) but for other body sites, with summer peaks and winter nadirs (P < 0.01). August showed the highest incidence, tripling that of February. Age groups 1-6 and 6-12 demonstrated the largest seasonal differences (P = 0.004, P = 0.008). Over three decades, paediatric hospitalized LC cases increased by 71% (P < 0.001), correlating with rising temperatures. Elevated ambient temperature seven days prior to diagnosis was a risk factor for LC development (OR = 1.02, P = 0.03). This study highlights the cyclic seasonal pattern of paediatric LC, peaking in summer. The significant increase in cases over time, coupled with rising temperatures, suggests climate change as a contributing factor. These findings could inform public health strategies for cellulitis prevention and management in children.

We consider time-inhomogeneous ordinary differential equations (ODEs) whose parameters are governed by an underlying ergodic Markov process. When this underlying process is accelerated by a factor $\varepsilon^{-1}$, an averaging phenomenon occurs and the solution of the ODE converges to a deterministic ODE as $\varepsilon$ vanishes. We are interested in cases where this averaged flow is globally attracted to a point. In that case, the equilibrium distribution of the solution of the ODE converges to a Dirac mass at this point. We prove an asymptotic expansion in terms of $\varepsilon$ for this convergence, with a somewhat explicit formula for the first-order term. The results are applied in three contexts: linear Markov-modulated ODEs, randomized splitting schemes, and Lotka–Volterra models in a random environment. In particular, as a corollary, we prove the existence of two matrices whose convex combinations are all stable but are such that, for a suitable jump rate, the top Lyapunov exponent of a Markov-modulated linear ODE switching between these two matrices is positive.

The strategy of tuberculosis (TB) contact investigation is essential for enhancing disease detection. We conducted a cross-sectional study to evaluate the yield of contact investigation for new TB cases, estimate the prevalence of TB, and identify characteristics of index cases associated with infection among contacts of new cases notified between 2010 and 2020 in São Paulo, Brazil. Out of 186466 index TB cases, 131055 (70.3%) underwent contact investigation. A total of 652286 contacts were screened, of which 451704 (69.2%) were examined. Of these, 12243 were diagnosed with active TB (yield of 1.9%), resulting in a number needed to screen of 53 and a number needed to test of 37 to identify one new TB case. The weighted prevalence for the total contacts screened was 2.8% (95% confidence interval [CI]: 2.7%–2.9%), suggesting underreporting of 6021 (95% CI: 5269–6673) cases. The likelihood of TB diagnosis was higher among contacts of cases identified through active case-finding, abnormal chest X-ray, pulmonary TB, or drug resistance, as well as among children, adults, women, individuals in socially vulnerable situations, and those with underlying clinical conditions. The study highlights significant TB underreporting among contacts, recommending strengthened contact investigation to promptly identify and treat new cases.

Research in decentralized computing, specifically in consensus algorithms, has focused on providing resistance to an adversary with a minority stake. This has resulted in systems that are majoritarian in the extreme, ignoring valuable lessons learned in law and politics over centuries. In this article, we first detail this phenomenon of majoritarianism and point out how minority protections in the nondigital world have been implemented. We motivate adding minority protections to collaborative systems with examples. We also show how current software deployment models exacerbate majoritarianism, highlighting the problem of monoculture in client software in particular. We conclude by giving some suggestions on how to make decentralized computing less hostile to those in the minority.

For a given graph $H$, we say that a graph $G$ has a perfect $H$-subdivision tiling if $G$ contains a collection of vertex-disjoint subdivisions of $H$ covering all vertices of $G.$ Let $\delta _{\mathrm {sub}}(n, H)$ be the smallest integer $k$ such that any $n$-vertex graph $G$ with minimum degree at least $k$ has a perfect $H$-subdivision tiling. For every graph $H$, we asymptotically determined the value of $\delta _{\mathrm {sub}}(n, H)$. More precisely, for every graph $H$ with at least one edge, there is an integer $\mathrm {hcf}_{\xi }(H)$ and a constant $1 \lt \xi ^*(H)\leq 2$ that can be explicitly determined by structural properties of $H$ such that $\delta _{\mathrm {sub}}(n, H) = \left (1 - \frac {1}{\xi ^*(H)} + o(1) \right )n$ holds for all $n$ and $H$ unless $\mathrm {hcf}_{\xi }(H) = 2$ and $n$ is odd. When $\mathrm {hcf}_{\xi }(H) = 2$ and $n$ is odd, then we show that $\delta _{\mathrm {sub}}(n, H) = \left (\frac {1}{2} + o(1) \right )n$.

This paper analyzes single-item continuous-review inventory models with random supplies in which the inventory dynamic between orders is described by a diffusion process, and a long-term average cost criterion is used to evaluate decisions. The models in this class have general drift and diffusion coefficients and boundary points that are consistent with the notion that demand should tend to reduce the inventory level. Random yield is described by a (probability) transition function which depends on the inventory on hand and the nominal amount ordered; it is assumed to be a distribution with support in the interval determined by the order-from and the nominal order-to locations of the stock level. Using weak convergence arguments involving average expected occupation and ordering measures, conditions are given for the optimality of an (s, S) ordering policy in the general class of policies with finite expected cost. The characterization of the cost of an (s, S) policy as a function of two variables naturally leads to a nonlinear optimization problem over the stock levels s and S, and the existence of an optimizing pair $(s^*,S^*)$ is established under weak conditions. Thus, optimal policies of inventory models with random supplies can (easily) be numerically computed. The range of applicability of the optimality result is illustrated on several inventory models with random yields.

Sexually transmitted infections caused by Chlamydia trachomatis (Ct) and Mycoplasma genitalium (Mg) have significant implications both at the individual and societal levels. Our study evaluated various co-factors associated with persistent serum IgG-antibodies to Ct and Mg. Three hundred and twenty nine pregnant women and 135 men from the Finnish Family HPV study were analyzed for serum IgG-antibodies of pGP3 for Ct and MgPa and rMgPa for Mg using multiplex serology. Seropersistence to both Ct and Mg was more common in women (30.4% and 13.3%) than in men (17.4% and 5.3%). The number of lifetime sexual partners above 10, the practice of anal sex, and a history of diagnosed Ct were associated with seropersistence to Ct in women, adjusted ORs 5.6 (95%CI 1.39–22.29), 15.3 (95%CI 1.18–197.12) and 18.0 (95%CI 5.59–57.92), respectively. The increasing number of partners before the age of 20 was the main risk factor for seropersistence among women with Mg, adjusted OR range from 5.0 to 12.3 (95%CI range 1.17–100.90) and in men only with 6–10 partners for Ct, adjusted OR 12.6 (95%CI 1.55–102.49). To conclude, persistent Ct antibodies were associated with various sexual activities, and Mg seropositivity was mainly associated with increased sexual activity in early adulthood.

We study the last exit time that a spectrally negative Lévy process is below zero until it reaches a positive level b, denoted by $g_{\tau_b^+}$. We generalize the results of the infinite-horizon last exit time explored by Chiu and Yin (2005) by incorporating a random horizon $\tau_b^+$, which represents the first passage time above b. We derive an explicit expression for the joint Laplace transform of $g_{\tau_b^+}$ and $\tau_b^+$ by utilizing a hybrid observation scheme approach proposed by Li, Willmot, and Wong (2018). We further study the optimal prediction of $g_{\tau_b^+}$ in the $L_1$ sense, and find that the optimal stopping time is the first passage time above a level $y_b^{\ast}$, with an explicit characterization of the stopping boundary $y_b^{\ast}$. As examples, Brownian motion with drift and the Cramér–Lundberg model with exponential jumps are considered.

An estimated 129000 cases of Lyme borreliosis (LB) are reported annually in Europe. In 2022, we conducted a representative web-based survey of 28034 persons aged 18–65 years old in 20 European countries to describe tick and LB risk exposures and perceptions. Nearly all respondents (95.0%) were aware of ticks (range, 90.4% in the UK to 98.8% in Estonia). Among those aware of ticks, most (85.1%) were also aware of LB (range, 70.3% in Switzerland to 97.0% in Lithuania). Overall, 8.3% of respondents reported a past LB diagnosis (range, 3.0% in Romania to 13.8% in Sweden). Respondents spent a weekly median of 7 (interquartile range [IQR] 3–14) hours in green spaces at home and 9 (IQR 4–16) hours away from home during April–November. The most common tick prevention measures always or often used were checking for ticks (44.8%) and wearing protective clothing (40.2%). This large multicountry survey provided needed data that can be used to design targeted LB prevention programmes in Europe.

We studied severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and vaccination status among six ethnic groups in Amsterdam, the Netherlands. We analysed participants of the Healthy Life in an Urban Setting cohort who were tested for SARS-CoV-2 spike protein antibodies between 17 May and 21 November 2022. We categorized participants with antibodies as only infected, only vaccinated (≥1 dose), or both infected and vaccinated, based on self-reported prior infection and vaccination status and previous seroprevalence data. We compared infection and vaccination status between ethnic groups using multivariable, multinomial logistic regression. Of the 1,482 included participants, 98.5% had SARS-CoV-2 antibodies (P between ethnic groups = 0.899). Being previously infected and vaccinated ranged from 36.2% (95% confidence interval (CI) = 28.3–44.1%) in the African Surinamese to 64.5% (95% CI = 52.9–76.1%) in the Ghanaian group. Compared to participants of Dutch origin, participants of South-Asian Surinamese (adjusted odds ratio (aOR) = 6.74, 95% CI = 2.61–17.45)), African Surinamese (aOR = 23.32, 95% CI = 10.55–51.54), Turkish (aOR = 8.50, 95% CI = 3.05–23.68), or Moroccan (aOR = 22.33, 95% CI = 9.48–52.60) origin were more likely to be only infected than infected and vaccinated, after adjusting for age, sex, household size, trust in the government’s response to the pandemic, and month of study visit. SARS-CoV-2 infection and vaccination status varied across ethnic groups, particularly regarding non-vaccination. As hybrid immunity is most protective against coronavirus disease 2019, future vaccination campaigns should encourage vaccination uptake in specific demographic groups with only infection.

For each uniformity $k \geq 3$, we construct $k$ uniform linear hypergraphs $G$ with arbitrarily large maximum degree $\Delta$ whose independence polynomial $Z_G$ has a zero $\lambda$ with $\left \vert \lambda \right \vert = O\left (\frac {\log \Delta }{\Delta }\right )$. This disproves a recent conjecture of Galvin, McKinley, Perkins, Sarantis, and Tetali.

Leptospira are bacteria that cause leptospirosis in both humans and animals. Human Leptospira infections in Uganda are suspected to arise from animal–human interactions. From a nationwide survey to determine Leptospira prevalence and circulating sequence types in Uganda, we tested 2030 livestock kidney samples, and 117 small mammals (rodents and shrews) using real-time PCR targeting the lipL32 gene. Pathogenic Leptospira species were detected in 45 livestock samples but not in the small mammals. The prevalence was 6.12% in sheep, 4.25% in cattle, 2.08% in goats, and 0.46% in pigs. Sequence typing revealed that Leptospira borgpetersenii, Leptospira kirschneri, and Leptospira interrogans are widespread across Uganda, with 13 novel sequence types identified. These findings enhance the East African MLST database and support the hypothesis that domesticated animals may be a source of human leptospirosis in Uganda, highlighting the need for increased awareness among those in close contact with livestock.

In July 2022, a genetically linked and geographically dispersed cluster of 12 cases of Shiga toxin-producing Escherichia coli (STEC) O103:H2 was detected by the UK Health Security Agency using whole genome sequencing. Review of food history questionnaires identified cheese (particularly an unpasteurized brie-style cheese) and mixed salad leaves as potential vehicles. A case–control study was conducted to investigate exposure to these products. Case food history information was collected by telephone. Controls were recruited using a market research panel and self-completed an online questionnaire. Univariable and multivariable analyses were undertaken using Firth Logistic Regression. Eleven cases and 24 controls were included in the analysis. Consumption of the brie-style cheese of interest was associated with illness (OR 57.5, 95% confidence interval: 3.10–1,060). Concurrently, the production of the brie-style cheese was investigated. Microbiological sample results for the cheese products and implicated dairy herd did not identify the outbreak strain, but did identify the presence of stx genes and STEC, respectively. Together, epidemiological, microbiological, and environmental investigations provided evidence that the brie-style cheese was the vehicle for this outbreak. Production of unpasteurized dairy products was suspended by the business operator, and a review of practices was performed.

We discuss the emerging technology of digital twins (DTs) and the expected demands as they scale to represent increasingly complex, interconnected systems. Several examples are presented to illustrate core use cases, highlighting a progression to represent both natural and engineered systems. The forthcoming challenges are discussed around a hierarchy of scales, which recognises systems of increasing aggregation. Broad implications are discussed, encompassing sensing, modelling, and deployment, alongside ethical and privacy concerns. Importantly, we endorse a modular and peer-to-peer view for aggregate (interconnected) DTs. This mindset emphasises that DT complexity emerges from the framework of connections (Wagg et al. [2024, The philosophical foundations of digital twinning, Preprint]) as well as the (interpretable) units that constitute the whole.