Optimal invasive species surveillance in the real world: practical advances from research

MGSurvE: A framework to optimize trap placement for genetic surveillance of mosquito populations

Genetic surveillance of mosquito populations is becoming increasingly relevant as genetics-based mosquito control strategies advance from laboratory to field testing. Especially applicable are mosquito gene drive projects, the potential scale of which leads monitoring to be a significant cost driver. For these projects, monitoring will be required to detect unintended spread of gene drive mosquitoes beyond field sites, and the emergence of alternative alleles, such as drive-resistant alleles or non-functional effector genes, within intervention sites. This entails the need to distribute mosquito traps efficiently such that an allele of interest is detected as quickly as possible-ideally when remediation is still viable. Additionally, insecticide-based tools such as bednets are compromised by insecticide-resistance alleles for which there is also a need to detect as quickly as possible. To this end, we present MGSurvE (Mosquito Gene SurveillancE): a computational framework that optimizes trap placement for genetic surveillance of mosquito populations such that the time to detection of an allele of interest is minimized. A key strength of MGSurvE is that it allows important biological features of mosquitoes and the landscapes they inhabit to be accounted for, namely: i) resources required by mosquitoes (e.g., food sources and aquatic breeding sites) can be explicitly distributed through a landscape, ii) movement of mosquitoes may depend on their sex, the current state of their gonotrophic cycle (if female) and resource attractiveness, and iii) traps may differ in their attractiveness profile. Example MGSurvE analyses are presented to demonstrate optimal trap placement for: i) an Aedes aegypti population in a suburban landscape in Queensland, Australia, and ii) an Anopheles gambiae population on the island of São Tomé, São Tomé and Príncipe. Further documentation and use examples are provided in project's documentation. MGSurvE is intended as a resource for both field and computational researchers interested in mosquito gene surveillance.

Optimal allocation of resources among general and species-specific tools for plant pest biosecurity surveillance

This paper proposes a surveillance model for plant pests that can optimally allocate resources among survey tools with varying properties. While some survey tools are highly specific for the detection of a single pest species, others are more generalized. There is considerable variation in the cost and sensitivity of these tools, but there are no guidelines or frameworks for identifying which tools are most cost-effective when used in surveillance programs that target the detection of newly invaded populations. To address this gap, we applied our model to design a trapping surveillance program in New Zealand for bark- and wood-boring insects, some of the most serious forest pests worldwide. Our findings show that exclusively utilizing generalized traps (GTs) proves to be highly cost-effective across a wide range of scenarios, particularly when they are capable of capturing all pest species. Implementing surveillance programs that only employ specialized traps (ST) is cost-effective only when these traps can detect highly damaging pests. However, even in such cases, they significantly lag in cost-effectiveness compared to GT-only programs due to their restricted coverage. When both GTs and STs are used in an integrated surveillance program, the total expected cost (TEC) generally diminishes when compared to programs relying on a single type of trap. However, this relative reduction in TEC is only marginally larger than that achieved with GT-only programs, as long as highly damaging species can be detected by GTs. The proportion of STs among the optimal required traps fluctuates based on several factors, including the relative pricing of GTs and STs, pest arrival rates, potential damage, and, more prominently, the coverage capacity of GTs. Our analysis suggests that deploying GTs extensively across landscapes appears to be more cost-effective in areas with either very high or very low levels of relative risk density, potential damage, and arrival rate. Finally, STs are less likely to be required when the pests that are detected by those tools have a higher likelihood of successful eradication because delaying detection becomes less costly for these species.

MGSurvE: A framework to optimize trap placement for genetic surveillance of mosquito population

Genetic surveillance of mosquito populations is becoming increasingly relevant as genetics-based mosquito control strategies advance from laboratory to field testing. Especially applicable are mosquito gene drive projects, the potential scale of which leads monitoring to be a significant cost driver. For these projects, monitoring will be required to detect unintended spread of gene drive mosquitoes beyond field sites, and the emergence of alternative alleles, such as drive-resistant alleles or non-functional effector genes, within intervention sites. This entails the need to distribute mosquito traps efficiently such that an allele of interest is detected as quickly as possible - ideally when remediation is still viable. Additionally, insecticide-based tools such as bednets are compromised by insecticide-resistance alleles for which there is also a need to detect as quickly as possible. To this end, we present MGSurvE (Mosquito Gene SurveillancE): a computational framework that optimizes trap placement for genetic surveillance of mosquito populations such that the time to detection of an allele of interest is minimized. A key strength of MGSurvE is that it allows important biological features of mosquitoes and the landscapes they inhabit to be accounted for, namely: i) resources required by mosquitoes (e.g., food sources and aquatic breeding sites) can be explicitly distributed through a landscape, ii) movement of mosquitoes may depend on their sex, the current state of their gonotrophic cycle (if female) and resource attractiveness, and iii) traps may differ in their attractiveness profile. Example MGSurvE analyses are presented to demonstrate optimal trap placement for: i) an Aedes aegypti population in a suburban landscape in Queensland, Australia, and ii) an Anopheles gambiae population on the island of São Tomé, São Tomé and Príncipe. Further documentation and use examples are provided in project's documentation. MGSurvE is freely available as an open-source Python package on pypi (https://pypi.org/project/MGSurvE/). It is intended as a resource for both field and computational researchers interested in mosquito gene surveillance.

Forest Insect Biosecurity: Processes, Patterns, Predictions, Pitfalls

The economic and environmental threats posed by non-native forest insects are ever increasing with the continuing globalization of trade and travel; thus, the need for mitigation through effective biosecurity is greater than ever. However, despite decades of research and implementation of preborder, border, and postborder preventative measures, insect invasions continue to occur, with no evidence of saturation, and are even predicted to accelerate. In this article, we review biosecurity measures used to mitigate the arrival, establishment, spread, and impacts of non-native forest insects and possible impediments to the successful implementation of these measures. Biosecurity successes are likely under-recognized because they are difficult to detect and quantify, whereas failures are more evident in the continued establishment of additional non-native species. There are limitations in existing biosecurity systems at global and country scales (for example, inspecting all imports is impossible, no phytosanitary measures are perfect, knownunknowns cannot be regulated against, and noncompliance is an ongoing problem). Biosecurity should be a shared responsibility across countries, governments, stakeholders, and individuals.

Monitoring Needs for Gene Drive Mosquito Projects: Lessons From Vector Control Field Trials and Invasive Species

As gene drive mosquito projects advance from contained laboratory testing to semi-field testing and small-scale field trials, there is a need to assess monitoring requirements to: i) assist with the effective introduction of the gene drive system at field sites, and ii) detect unintended spread of gene drive mosquitoes beyond trial sites, or resistance mechanisms and non-functional effector genes that spread within trial and intervention sites. This is of particular importance for non-localized gene drive projects, as the potential scale of intervention means that monitoring is expected to be more costly than research, development and deployment. Regarding monitoring needs for population replacement systems, lessons may be learned from experiences with Wolbachia-infected mosquitoes, and for population suppression systems, from experiences with releases of genetically sterile male mosquitoes. For population suppression systems, assessing monitoring requirements for tracking population size and detecting rare resistant alleles are priorities, while for population replacement systems, allele frequencies must be tracked, and pressing concerns include detection of gene drive alleles with non-functional effector genes, and resistance of pathogens to functional effector genes. For spread to unintended areas, open questions relate to the optimal density and placement of traps and frequency of sampling in order to detect gene drive alleles, drive-resistant alleles or non-functional effector genes while they can still be effectively managed. Invasive species management programs face similar questions, and lessons may be learned from these experiences. We explore these monitoring needs for gene drive mosquito projects progressing through the phases of pre-release, release and post-release.

Biosecurity: tools, behaviours and concepts

COVID 19 has raised the profile of biosecurity. However, biosecurity is not only about protecting human life. This issue brings together mini-reviews examining recent developments and thinking around some of the tools, behaviours and concepts around biosecurity. They illustrate the multi-disciplinary nature of the subject, demonstrating the interface between research and policy. Biosecurity practices aim to prevent the spread of harmful organisms; recognising that 2020 is the International Year of Plant Health, several focus on plant biosecurity although invasive species and animal health concerns are also captured. The reviews show progress in developing early warning systems and that plant protection organisations are increasingly using tools that compare multiple pest threats to prioritise responses. The bespoke modelling of threats can inform risk management responses and synergies between meteorology and biosecurity provide opportunities for increased collaboration. There is scope to develop more generic models, increasing their accessibility to policy makers. Recent research can improve pest surveillance programs accounting for real-world constraints. Social science examining individual farmer behaviours has informed biosecurity policy; taking a broader socio-cultural approach to better understand farming networks has the potential to change behaviours in a new way. When encouraging public recreationists to adopt positive biosecurity behaviours communications must align with their values. Bringing together the human, animal, plant and environmental health sectors to address biosecurity risks in a common and systematic manner within the One Biosecurity concept can be achieved through multi-disciplinary working involving the life, physical and social sciences with the support of legislative bodies and the public.