Michael Alastair Irvine

Quantitative analyses and modelling to support achievement of the 2020 goals for nine neglected tropical diseases

Quantitative analysis and mathematical models are useful tools in informing strategies to control or eliminate disease. Currently, there is an urgent need to develop these tools to inform policy to achieve the 2020 goals for neglected tropical diseases (NTDs). In this paper we give an overview of a collection of novel model-based analyses which aim to address key questions on the dynamics of transmission and control of nine NTDs: Chagas disease, visceral leishmaniasis, human African trypanosomiasis, leprosy, soil-transmitted helminths, schistosomiasis, lymphatic filariasis, onchocerciasis and trachoma. Several common themes resonate throughout these analyses, including: the importance of epidemiological setting on the success of interventions; targeting groups who are at highest risk of infection or re-infection; and reaching populations who are not accessing interventions and may act as a reservoir for infection,. The results also highlight the challenge of maintaining elimination ‘as a public health problem’ when true elimination is not reached. The models elucidate the factors that may be contributing most to persistence of disease and discuss the requirements for eventually achieving true elimination, if that is possible. Overall this collection presents new analyses to inform current control initiatives. These papers form a base from which further development of the models and more rigorous validation against a variety of datasets can help to give more detailed advice. At the moment, the models’ predictions are being considered as the world prepares for a final push towards control or elimination of neglected tropical diseases by 2020.

Effectiveness of a triple-drug regimen for global elimination of lymphatic filariasis: a modelling study

BACKGROUND Lymphatic filariasis is targeted for elimination as a public health problem by 2020. The principal approach used by current programmes is annual mass drug administration with two pairs of drugs with a good safety profile. However, one dose of a triple-drug regimen (ivermectin, diethylcarbamazine, and albendazole) has been shown to clear the transmissible stage of the helminth completely in treated individuals. The aim of this study was to use modelling to assess the potential value of mass drug administration with the triple-drug regimen for accelerating elimination of lymphatic filariasis in different epidemiological settings. METHODS We used three different transmission models to compare the number of rounds of mass drug administration needed to achieve a prevalence of microfilaraemia less than 1% with the triple-drug regimen and with current two-drug regimens. FINDINGS In settings with a low baseline prevalence of lymphatic filariasis (5%), the triple-drug regimen reduced the number of rounds of mass drug administration needed to reach the target prevalence by one or two rounds, compared with the two-drug regimen. For areas with higher baseline prevalence (10-40%), the triple-drug regimen strikingly reduced the number of rounds of mass drug administration needed, by about four or five, but only at moderate-to-high levels of population coverage (>65%) and if systematic non-adherence to mass drug administration was low. INTERPRETATION Simulation modelling suggests that the triple-drug regimen has potential to accelerate the elimination of lymphatic filariasis if high population coverage of mass drug administration can be achieved and if systematic non-adherence with mass drug administration is low. Future work will reassess these estimates in light of more clinical trial data and to understand the effect on an individual countrys programme. FUNDING Bill & Melinda Gates Foundation.

Predicting lymphatic filariasis transmission and elimination dynamics using a multi-model ensemble framework

Highlights • No single mathematical model captures all features of parasite transmission dynamics.• Multi-model ensemble modelling can overcome biases of single models.• A multi-model ensemble of three lymphatic filariasis models is proposed and evaluated.• The multi-model ensemble outperformed the single models in predicting infection.• The ensemble approach may improve use of models to inform disease control policy.

Cost-effectiveness of screening for HIV in primary care : a health economics modelling analysis

Summary Background Early HIV diagnosis reduces morbidity, mortality, the probability of onward transmission, and their associated costs, but might increase cost because of earlier initiation of antiretroviral treatment (ART). We investigated this trade-off by estimating the cost-effectiveness of HIV screening in primary care. Methods We modelled the effect of the four-times higher diagnosis rate observed in the intervention arm of the RHIVA2 randomised controlled trial done in Hackney, London (UK), a borough with high HIV prevalence (≥0·2% adult prevalence). We constructed a dynamic, compartmental model representing incidence of infection and the effect of screening for HIV in general practices in Hackney. We assessed cost-effectiveness of the RHIVA2 trial by fitting model diagnosis rates to the trial data, parameterising with epidemiological and behavioural data from the literature when required, using trial testing costs and projecting future costs of treatment. Findings Over a 40 year time horizon, incremental cost-effectiveness ratios were £22 201 (95% credible interval 12 662–132 452) per quality-adjusted life-year (QALY) gained, £372 207 (268 162–1 903 385) per death averted, and £628 874 (434 902–4 740 724) per HIV transmission averted. Under this model scenario, with UK cost data, RHIVA2 would reach the upper National Institute for Health and Care Excellence cost-effectiveness threshold (about £30 000 per QALY gained) after 33 years. Scenarios using cost data from Canada (which indicate prolonged and even higher health-care costs for patients diagnosed late) suggest this threshold could be reached in as little as 13 years. Interpretation Screening for HIV in primary care has important public health benefits as well as clinical benefits. We predict it to be cost-effective in the UK in the medium term. However, this intervention might be cost-effective far sooner, and even cost-saving, in settings where long-term health-care costs of late-diagnosed patients in high-prevalence regions are much higher (≥60%) than those of patients diagnosed earlier. Screening for HIV in primary care is cost-effective and should be promoted. Funding NHS City and Hackney, UK Department of Health, National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care.

Distribution of take-home opioid antagonist kits during a synthetic opioid epidemic in British Columbia, Canada: a modelling study

BACKGROUND Illicit use of high-potency synthetic opioids has become a global issue over the past decade. This misuse is particularly pronounced in British Columbia, Canada, where a rapid increase in availability of fentanyl and other synthetic opioids in the local illicit drug supply during 2016 led to a substantial increase in overdoses and deaths. In response, distribution of take-home naloxone (THN) overdose prevention kits was scaled up (6·4-fold increase) throughout the province. The aim of this study was to estimate the impact of the THN programme in terms of the number of deaths averted over the study period. METHODS We estimated the impact of THN kits on the ongoing epidemic among people who use illicit opioids in British Columbia and explored counterfactual scenarios for the provincial response. A Markov chain model was constructed explicitly including opioid-related deaths, fentanyl-related deaths, ambulance-attended overdoses, and uses of THN kits. The model was calibrated in a Bayesian framework incorporating population data between Jan 1, 2012, and Oct 31, 2016. FINDINGS 22 499 ambulance-attended overdoses and 2121 illicit drug-related deaths (677 [32%] deaths related to fentanyl) were recorded in the study period, mostly since January, 2016. In the same period, 19 074 THN kits were distributed. We estimate that 298 deaths (95% credible interval [CrI] 91-474) were averted by the THN programme. Of these deaths, 226 (95% CrI 125-340) were averted in 2016, following a rapid scale-up in distribution of kits. We infer a rapid increase in fentanyl adulterant at the beginning of 2016, with an estimated 2·3 times (95% CrI 2·0-2·9) increase from 2015 to 2016. Counterfactual modelling indicated that an earlier scale-up of the programme would have averted an additional 118 deaths (95% CrI 64-207). Our model also indicated that the increase in deaths could parsimoniously be explained through a change in the fentanyl-related overdose rate alone. INTERPRETATION The THN programme substantially reduced the number of overdose deaths during a period of rapid increase in the number of illicit drug overdoses due to fentanyl in British Columbia. However, earlier adoption and distribution of the THN intervention might have had an even greater impact on overdose deaths. Our findings show the value of a fast and effective response at the start of a synthetic opioid epidemic. We also believe that multiple interventions are needed to achieve an optimal impact. FUNDING Canadian Institutes of Health Research Partnerships for Health Systems Improvement programme (grant 318068) and Natural Science and Engineering Research Council of Canada (grant 04611).

Understanding heterogeneities in mosquito-bite exposure and infection distributions for the elimination of lymphatic filariasis

It is well known that individuals in the same community can be exposed to a highly variable number of mosquito bites. This heterogeneity in bite exposure has consequences for the control of vector-borne diseases because a few people may be contributing significantly to transmission. However, very few studies measure sources of heterogeneity in a way which is relevant to decision-making. We investigate the relationship between two classic measures of heterogeneity, spatial and individual, within the context of lymphatic filariasis, a parasitic mosquito-borne disease. Using infection and mosquito-bite data for five villages in Papua New Guinea, we measure biting characteristics to model what impact bed-nets have had on control of the disease. We combine this analysis with geospatial modelling to understand the spatial relationship between disease indicators and nightly mosquito bites. We found a weak association between biting and infection heterogeneity within villages. The introduction of bed-nets increased biting heterogeneity, but the reduction in mean biting more than compensated for this, by reducing prevalence closer to elimination thresholds. Nightly biting was explained by a spatial heterogeneity model, while parasite load was better explained by an individual heterogeneity model. Spatial and individual heterogeneity are qualitatively different with profoundly different policy implications.

Aggregation dynamics explain vegetation patch-size distributions

Vegetation patch-size distributions have been an intense area of study for theoreticians and applied ecologists alike in recent years. Of particular interest is the seemingly ubiquitous nature of power-law patch-size distributions emerging in a number of diverse ecosystems. The leading explanation of the emergence of these power-laws is due to local facilitative mechanisms. There is also a common transition from power law to exponential distribution when a system is under global pressure, such as grazing or lack of rainfall. These phenomena require a simple mechanistic explanation. Here, we study vegetation patches from a spatially implicit, patch dynamic viewpoint. We show that under minimal assumptions a power-law patch-size distribution appears as a natural consequence of aggregation. A linear death term also leads to an exponential term in the distribution for any non-zero death rate. This work shows the origin of the breakdown of the power-law under increasing pressure and shows that in general, we expect to observe a power law with an exponential cutoff (rather than pure power laws). The estimated parameters of this distribution also provide insight into the underlying ecological mechanisms of aggregation and death.

Fractal measures of spatial pattern as a heuristic for return rate in vegetative systems

Measurement of population persistence is a long-standing problem in ecology; in particular, whether it is possible to gain insights into persistence without long time-series. Fractal measurements of spatial patterns, such as the Korcak exponent or boundary dimension, have been proposed as indicators of the persistence of underlying dynamics. Here we explore under what conditions a predictive relationship between fractal measures and persistence exists. We combine theoretical arguments with an aerial snapshot and time series from a long-term study of seagrass. For this form of vegetative growth, we find that the expected relationship between the Korcak exponent and persistence is evident at survey sites where the population return rate can be measured. This highlights a limitation of the use of power-law patch-size distributions and other indicators based on spatial snapshots. Moreover, our numeric simulations show that for a single species and a range of environmental conditions that the Korcak–persistence relationship provides a link between temporal dynamics and spatial pattern; however, this relationship is specific to demographic factors, so we cannot use this methodology to compare between species.

Disease transmission promotes evolution of host spatial patterns

Ecological dynamics can produce a variety of striking patterns. On ecological time scales, pattern formation has been hypothesized to be due to the interaction between a species and its local environment. On longer time scales, evolutionary factors must be taken into account. To examine the evolutionary robustness of spatial pattern formation, we construct a spatially explicit model of vegetation in the presence of a pathogen. Initially, we compare the dynamics for vegetation parameters that lead to competition induced spatial patterns and those that do not. Over ecological time scales, banded spatial patterns dramatically reduced the ability of the pathogen to spread, lowered its endemic density and hence increased the persistence of the vegetation. To gain an evolutionary understanding, each plant was given a heritable trait defining its resilience to competition; greater competition leads to lower vegetation density but stronger spatial patterns. When a disease is introduced, the selective pressure on the plants resilience to the competition parameter is determined by the transmission of the disease. For high transmission, vegetation that has low resilience to competition and hence strong spatial patterning is an evolutionarily stable strategy. This demonstrates a novel mechanism by which striking spatial patterns can be maintained by disease-driven selection.

Are alternative strategies required to accelerate the global elimination of lymphatic filariasis? Insights from mathematical models

Abstract Background With the 2020 target year for elimination of lymphatic filariasis (LF) approaching, there is an urgent need to assess how long mass drug administration (MDA) programs with annual ivermectin + albendazole (IA) or diethylcarbamazine + albendazole (DA) would still have to be continued, and how elimination can be accelerated. We addressed this using mathematical modeling. Methods We used 3 structurally different mathematical models for LF transmission (EPIFIL, LYMFASIM, TRANSFIL) to simulate trends in microfilariae (mf) prevalence for a range of endemic settings, both for the current annual MDA strategy and alternative strategies, assessing the required duration to bring mf prevalence below the critical threshold of 1%. Results Three annual MDA rounds with IA or DA and good coverage (≥65%) are sufficient to reach the threshold in settings that are currently at mf prevalence <4%, but the required duration increases with increasing mf prevalence. Switching to biannual MDA or employing triple-drug therapy (ivermectin, diethylcarbamazine, and albendazole [IDA]) could reduce program duration by about one-third. Optimization of coverage reduces the time to elimination and is particularly important for settings with a history of poorly implemented MDA (low coverage, high systematic noncompliance). Conclusions Modeling suggests that, in several settings, current annual MDA strategies will be insufficient to achieve the 2020 LF elimination targets, and programs could consider policy adjustment to accelerate, guided by recent monitoring and evaluation data. Biannual treatment and IDA hold promise in reducing program duration, provided that coverage is good, but their efficacy remains to be confirmed by more extensive field studies.