Antimicrobial resistance (AMR) is a growing One Health crisis that can be impacted by other challenges of sustainable development, such as climate change, but few interventions have been assessed with a systems-wide lens. The objectives of this study were to use a previously defined fuzzy cognitive map (FCM) of the Swedish One Health system to: 1) identify areas in the system to target interventions; and 2) test the potential ability and viability of interventions to reduce AMR under a changing climate. The FCM, based on participatory modelling workshops and literature scan, was used to assess the sustainability of eight interventions under potential climate change conditions. Network metrics were calculated to describe the system structure and identify highly impactful nodes. The network metrics identified high-leverage nodes including alternative productions systems and good farming practices. None of the scenarios evaluated were able to adequately reduce AMR within the system. Overall, fuzzy cognitive mapping provides an innovative way to analyse the AMR system, identify high-leverage interventions, and examine potential impact of interventions using a broader systems lens.

Dengue infection in China has increased dramatically in recent years. Guangdong province (main city Guangzhou) accounted for more than 94% of all dengue cases in the 2014 outbreak. Currently, there is no existing effective vaccine and most efforts of control are focused on the vector itself. This study aimed to evaluate different dengue management strategies in a region where this disease is emerging. This work was done by establishing a dengue simulation model for Guangzhou to enable the testing of control strategies aimed at vector control and vaccination. For that purpose, the computer-based dengue simulation model (DENSiM) together with the Container-Inhabiting Mosquito Simulation Model (CIMSiM) has been used to create a working dengue simulation model for the city of Guangzhou. In order to achieve the best model fit against historical surveillance data, virus introduction scenarios were run and then matched against the actual dengue surveillance data. The simulation model was able to predict retrospective outbreaks with a sensitivity of 0.18 and a specificity of 0.98. This new parameterisation can now be used to evaluate the potential impact of different control strategies on dengue transmission in Guangzhou. The knowledge generated from this research would provide useful information for authorities regarding the historic patterns of dengue outbreaks, as well as the effectiveness of different disease management strategies.

In this study we apply an evidence-based approach to model population-size fluctuations and their corresponding impact on land use during the Roman and early-medieval periods in the Rhine–Meuse delta in the present-day Netherlands. Past-population numbers are reconstructed based on Roman and early-medieval settlement patterns. Corresponding impacts of these demographic fluctuations on potential land use are calculated by integrating the newly developed demographic overviews with archaeological and geoscientific data using a new land-use model termed ‘Past Land-Use Scanner’ (PLUS). The primary aims are to reconstruct first-millennium palaeodemographics and to explore the potential of simulation modelling for testing the feasibility of archaeological hypotheses regarding past land use. Results show that in the study area the first millennium AD was characterised by two periods during which major population growth occurred: the middle-Roman period (AD 70–270) and early-medieval period C (AD 725–950). A major demographic decline of 78–85% occurred during the late-Roman period (AD 270–450), after which first-millennium population numbers never again reached middle-Roman period levels. The modelling outcomes demonstrate that the impact of population fluctuations (growth vs decline) on the limits of the natural landscape during the first millennium in general was low. During these thousand years, the natural landscape almost without exception (only scenario D deviates) provided sufficient options for arable farming, meadows and pastures and was not a limiting factor for population growth. These results underline the added value of simulation modelling for testing the feasibility of archaeological hypotheses and analysing human–landscape interactions in the past.

Emerging and re-emerging infectious disease (EID) events can have devastating human, animal and environmental health impacts. The emergence of EIDs has been associated with interconnected economic, social and environmental changes. Understanding these changes is crucial for EID preparedness and subsequent prevention and control of EID events. The aim of this review is to describe tools currently available for identification, prioritization and investigation of EIDs impacting human and animal health, and how these might be integrated into a systematic approach for directing EID preparedness. Environmental scanning, foresight programmes, horizon scanning and surveillance are used to collect and assess information for rapidly responding to EIDs and to anticipate drivers of emergence for mitigating future EID impacts. Prioritization of EIDs − using transparent and repeatable methods − based on disease impacts and the importance of those impacts to decision-makers can then be used for more efficient resource allocation for prevention and control. Risk assessment and simulation modelling methods assess the likelihood of EIDs occurring, define impact and identify mitigation strategies. Each of these tools has a role to play individually; however, we propose integration of these tools into a framework that enhances the development of tactical and strategic plans for emerging risk preparedness.

Refugia-based treatment strategies aim to prolong anthelmintic efficacy by maintaining a parasite population unexposed to anthelmintics. Targeted selective treatment (TST) achieves this by treating only animals that will benefit most from treatment, using a determinant criterion (DC). We developed a mathematical model to compare various traits proposed as DC, and investigate impacts of TST and drenching frequency on sheep performance and anthelmintic resistance. Short term, decreasing the proportion of animals drenched reduced benefits of anthelmintic treatment, assessed by empty body weight (EBW), but decreased the rate of anthelmintic resistance development; each consecutive drenching had a reduced impact on average EBW and an increased impact on the rate of anthelmintic resistance emergences. The optimal DC was fecal egg count, maintaining the highest average EBW when reducing the proportion of animals drenched. Long-term, reducing the proportion of animals drenched had little impact on total weight gain benefits, across animals and years, whilst reducing drenching frequency increased it. Decreasing the frequency and proportion of animals drenched were both predicted to increase the duration of anthelmintic efficacy but reduce the total number of drenches administered before resistance was observed. TST and frequency of drenching may lead to different benefits in the short versus long term.