Risk factors for tick attachment in companion animals in Great Britain: a spatiotemporal analysis covering 2014-2021.

BACKGROUND: Ticks are an important driver of veterinary health care, causing irritation and sometimes infection to their hosts. We explored epidemiological and geo-referenced data from > 7 million electronic health records (EHRs) from cats and dogs collected by the Small Animal Veterinary Surveillance Network (SAVSNET) in Great Britain (GB) between 2014 and 2021 to assess the factors affecting tick attachment in an individual and at a spatiotemporal level. METHODS: EHRs in which ticks were mentioned were identified by text mining; domain experts confirmed those with ticks on the animal. Tick presence/absence records were overlaid with a spatiotemporal series of climate, environment, anthropogenic and host distribution factors to produce a spatiotemporal regression matrix. An ensemble machine learning spatiotemporal model was used to fine-tune hyperparameters for Random Forest, Gradient-boosted Trees and Generalized Linear Model regression algorithms, which were then used to produce a final ensemble meta-learner to predict the probability of tick attachment across GB at a monthly interval and averaged long-term through 2014-2021 at a spatial resolution of 1 km. Individual host factors associated with tick attachment were also assessed by conditional logistic regression on a matched case-control dataset. RESULTS: In total, 11,741 consultations were identified in which a tick was recorded. The frequency of tick records was low (0.16% EHRs), suggesting an underestimation of risk. That said, increased odds for tick attachment in cats and dogs were associated with younger adult ages, longer coat length, crossbreeds and unclassified breeds. In cats, males and entire animals had significantly increased odds of recorded tick attachment. The key variables controlling the spatiotemporal risk for tick attachment were climatic (precipitation and temperature) and vegetation type (Enhanced Vegetation Index). Suitable areas for tick attachment were predicted across GB, especially in forests and grassland areas, mainly during summer, particularly in June. CONCLUSIONS: Our results can inform targeted health messages to owners and veterinary practitioners, identifying those animals, seasons and areas of higher risk for tick attachment and allowing for more tailored prophylaxis to reduce tick burden, inappropriate parasiticide treatment and potentially TBDs in companion animals and humans. Sentinel networks like SAVSNET represent a novel complementary data source to improve our understanding of tick attachment risk for companion animals and as a proxy of risk to humans.

Geospatial modelling of lymphatic filariasis and malaria co-endemicity in Nigeria.

BACKGROUND: Lymphatic filariasis (LF) and malaria are important vector-borne diseases that are co-endemic throughout Nigeria. These infections are transmitted by the same mosquito vector species in Nigeria and their transmission is similarly influenced by climate and sociodemographic factors. The goal of this study was to assess the relationship between the geospatial distribution of both infections in Nigeria to better coordinate interventions. METHODS: We used national survey data for malaria from the Demographic and Health Survey dataset and site-level LF mapping data from the Nigeria Lymphatic Filariasis Control Programme together with a suite of predictive climate and sociodemographic factors to build geospatial machine learning models. These models were then used to produce continuous gridded maps of both infections throughout Nigeria. RESULTS: The R2 values for the LF and malaria models were 0.68 and 0.59, respectively. Also, the correlation between pairs of observed and predicted values for LF and malaria models were 0.69 (95% confidence interval [CI] 0.61 to 0.79; p<0.001) and 0.61 (95% CI 0.52 to 0.71; p<0.001), respectively. However, we observed a very weak positive correlation between overall overlap of LF and malaria distribution in Nigeria. CONCLUSIONS: The reasons for this counterintuitive relationship are unclear. Differences in transmission dynamics of these parasites and vector competence may contribute to differences in the distribution of these co-endemic diseases.

Comparing antigenaemia- and microfilaraemia as criteria for stopping decisions in lymphatic filariasis elimination programmes in Africa.

BACKGROUND: Mass drug administration (MDA) is the main strategy towards lymphatic filariasis (LF) elimination. Progress is monitored by assessing microfilaraemia (Mf) or circulating filarial antigenaemia (CFA) prevalence, the latter being more practical for field surveys. The current criterion for stopping MDA requires <2% CFA prevalence in 6- to 7-year olds, but this criterion is not evidence-based. We used mathematical modelling to investigate the validity of different thresholds regarding testing method and age group for African MDA programmes using ivermectin plus albendazole. METHODOLGY/PRINCIPAL FINDINGS: We verified that our model captures observed patterns in Mf and CFA prevalence during annual MDA, assuming that CFA tests are positive if at least one adult worm is present. We then assessed how well elimination can be predicted from CFA prevalence in 6-7-year-old children or from Mf or CFA prevalence in the 5+ or 15+ population, and determined safe (>95% positive predictive value) thresholds for stopping MDA. The model captured trends in Mf and CFA prevalences reasonably well. Elimination cannot be predicted with sufficient certainty from CFA prevalence in 6-7-year olds. Resurgence may still occur if all children are antigen-negative, irrespective of the number tested. Mf-based criteria also show unfavourable results (PPV <95% or unpractically low threshold). CFA prevalences in the 5+ or 15+ population are the best predictors, and post-MDA threshold values for stopping MDA can be as high as 10% for 15+. These thresholds are robust for various alternative assumptions regarding baseline endemicity, biological parameters and sampling strategies. CONCLUSIONS/SIGNIFICANCE: For African areas with moderate to high pre-treatment Mf prevalence that have had 6 or more rounds of annual ivermectin/albendazole MDA with adequate coverage, we recommend to adopt a CFA threshold prevalence of 10% in adults (15+) for stopping MDA. This could be combined with Mf testing of CFA positives to ensure absence of a significant Mf reservoir for transmission.

Persistence of onchocerciasis in villages in Enugu and Ogun states in Nigeria following many rounds of mass distribution of ivermectin.

BACKGROUND: Onchocerciasis is endemic in most local government areas (LGAs) in Enugu and Ogun states. Most meso- and hyper-endemic LGAs have received many rounds of ivermectin mass drug administration (MDA). This study aimed to determine the current prevalence of onchocerciasis in villages in Enugu and Ogun states that were formerly highly endemic and to assess progress toward elimination of the infection in areas believed to be at high risk for persistence. METHODS: Cross-sectional community surveys were conducted 8 to 12 months after the last round of MDA in 16 villages (6 in Enugu state and 10 in Ogun state) in individuals aged ≥ 18 years. Study participants were examined for the presence of palpable subcutaneous nodules. Skin snips from the posterior iliac crests were used to assess microfiladermia (Mf) prevalence and density. RESULTS: 643 subjects were palpated for nodules and 627 individuals (225 in Enugu state; 402 in Ogun state) provided skin snips. Nodule prevalence in the study villages ranged from 42 to 66.7% in Enugu state and from 0 to 25.0% in Ogun state. Mf prevalence in the Enugu and Ogun study villages ranged from 32 to 51.1% and 0 to 28.6%, respectively. Geometric mean skin Mf density in surveyed Enugu state villages ranged between 1 and 3.1 Mf/mg; these values were < 1 Mf/mg in all but one community in Ogun state villages. CONCLUSION: Results from this study show that onchocerciasis persists in adults in many villages in Enugu and Ogun states despite many prior rounds of ivermectin MDA. Prevalence was higher in villages surveyed in Enugu than in Ogun. Low Mf densities suggest the MDA program is working well to reduce disease, but more time will be required to reach the elimination goal.

Community-based trial assessing the impact of annual versus semiannual mass drug administration with ivermectin plus albendazole and praziquantel on helminth infections in northwestern Liberia.

We assessed the impact of three annual vs five semiannual rounds of mass drug administration (MDA) with ivermectin plus albendazole followed by praziquantel for the control or elimination of lymphatic filariasis (LF), onchocerciasis, soil-transmitted helminth (STH) infections and schistosomiasis in Lofa County, Liberia. The study started in 2012 and was interrupted in 2014 during the Ebola virus outbreak. Repeated cross-sectional surveys were conducted in individuals 5 years and older to measure infection markers. Wuchereria bancrofti antigenemia prevalences decreased from 12.5 to 1.2% (90% reduction) and from 13.6 to 4.2% (69% reduction) one year after three rounds of annual or five rounds of semiannual MDA, respectively. Mixed effects logistic regression models showed decreases in odds of antigenemia positivity were 91 and 74% at that time in the annual and semiannual treatment zones, respectively (p < 0.001). Semiannual MDA was slightly more effective for reducing Onchocerca volvulus microfiladermia prevalence and at follow-up 3 were 74% (from 14.4 to 3.7%) and 83% (from 23.6 to 4.5%) in the annual and semiannual treatment zones, respectively. Both treatment schedules had similar beneficial effects on hookworm prevalence. Thus, annual and semiannual MDA with ivermectin and albendazole had similar beneficial impacts on LF, onchocerciasis, and STH in this setting. In contrast, MDA with praziquantel had little impact on hyperendemic Schistosoma mansoni in the study area. Results from a long-term follow-up survey showed that improvements in infection parameters were sustained by routine annual MDA provided by the Liberian Ministry of Health after our study endpoint.

Impact of Annual versus Semiannual Mass Drug Administration with Ivermectin and Albendazole on Helminth Infections in Southeastern Liberia.

We compared the impact of three rounds of annual and five rounds of semiannual mass drug administration (MDA) with albendazole plus ivermectin on helminthic infections in Liberia. Repeated annual cross-sectional community surveys were conducted between 2013 and 2019 in individuals of 5 years and older. Primary outcome was the change of infection prevalence estimates from baseline to month 36 (12 months after the last treatment). After three rounds of annual MDA, Wuchereria bancrofti circulating filarial antigen (CFA) and microfilaria (Mf) prevalence estimates decreased from 19.7% to 4.3% and from 8.6% to 0%, respectively; after semiannual MDA, CFA and Mf prevalences decreased from 37.8% to 16.8% and 17.9% to 1%, respectively. Mixed effects logistic regression models indicated that the odds of having Mf decreased by 97% (P < 0.001) at month 36 (similar odds for annual and semiannual MDA zones). A parallel analysis showed that the odds of CFA were reduced by 83% and 69% at 36 months in the annual and semiannual treatment zones, respectively (P < 0.001). Onchocerca volvulus Mf prevalence decreased slightly after multiple MDA rounds in both treatment zones. Reductions in hookworm and Trichuris trichiura prevalences and intensities were slightly greater in the annual treatment zone. Ascaris lumbricoides prevalence rates were relatively unchanged, although infection intensities decreased sharply throughout. Results show that annual and semiannual MDA were equally effective for reducing LF and soil-transmitted helminth infection parameters over a 3-year period, and reductions recorded at month 36 were sustained by routine annual MDA through month 72.

Progress towards onchocerciasis elimination in Côte d'Ivoire: A geospatial modelling study.

BACKGROUND: Côte d'Ivoire has had 45 years of intervention for onchocerciasis by vector control (from 1975 to 1991), ivermectin mass drug administration (MDA) (from 1992 to 1994) and community directed treatment with ivermectin (CDTi) from 1995 to the present. We modeled onchocerciasis endemicity during two time periods that correspond to the scale up of vector control and ivermectin distribution, respectively. This analysis illustrates progress towards elimination during these periods, and it has identified potential hotspots areas that are at risk for ongoing transmission. METHODS AND FINDINGS: The analysis used Ministry of Health skin snip microfilaria (MF) prevalence and intensity data collected between 1975 and 2016. Socio-demographic and environmental factors were incorporated into a predictive, machine learning algorithm to create continuous maps of onchocerciasis endemicity. Overall predicted mean MF prevalence decreased from 51.8% circa 1991 to 3.9% circa 2016. The model predicted infection foci with higher prevalence in the southern region of the country. Predicted mean community MF load (CMFL) decreased from 10.1MF/snip circa 1991 to 0.1MF/snip circa 2016. Again, the model predicts foci with higher Mf densities in the southern region. For assessing model performance, the root mean squared error and R2 values were 1.14 and 0.62 respectively for a model trained with data collected prior to 1991, and 1.28 and 0.57 for the model trained with infection survey data collected later, after the introduction of ivermectin. Finally, our models show that proximity to permanent inland bodies of water and altitude were the most informative variables that correlated with onchocerciasis endemicity. CONCLUSION/SIGNIFICANCE: This study further documents the significant reduction of onchocerciasis infection following widespread use of ivermectin for onchocerciasis control in Côte d'Ivoire. Maps produced predict areas at risk for ongoing infection and transmission. Onchocerciasis might be eliminated in Côte d'Ivoire in the future with a combination of sustained CDTi with high coverage, active surveillance, and close monitoring for persistent infection in previously hyper-endemic areas.

Multilevel modelling of the risk of malaria among children aged under five years in Nigeria.

BACKGROUND: Malaria is still a major cause of morbidity and mortality among children aged <5 y (U5s). This study assessed individual, household and community risk factors for malaria in Nigerian U5s. METHODS: Data from the Nigerian Malaria Health Indicator Survey 2015 were pooled for analyses. This comprised a national survey of 329 clusters. Children aged 6-59 mo who were tested for malaria using microscopy were retained. Multilevel logit model accounting for sampling design was used to assess individual, household and community factors associated with malaria parasitaemia. RESULTS: A total of 5742 children were assessed for malaria parasitaemia with an overall prevalence of 27% (95% CI 26 to 28%). Plasmodium falciparum constituted 98% of the Plasmodium species. There was no significant difference in parasitaemia between older children and those aged ≤12 mo. In adjusted analyses, rural living, northwest region, a household size of >7, dependence on river and rainwater as primary water source were associated with higher odds of parasitaemia, while higher wealth index, all U5s who slept under a bed net and dependence on packaged water were associated with lower odds of parasitaemia. CONCLUSION: Despite sustained investment in malaria control and prevention, a quarter of the overall study population of U5s have malaria. Across the six geopolitical zones, the highest burden was in children living in the poorest rural households.

Mapping the baseline prevalence of lymphatic filariasis across Nigeria.

INTRODUCTION: The baseline endemicity profile of lymphatic filariasis (LF) is a key benchmark for planning control programmes, monitoring their impact on transmission and assessing the feasibility of achieving elimination. Presented in this work is the modelled serological and parasitological prevalence of LF prior to the scale-up of mass drug administration (MDA) in Nigeria using a machine learning based approach. METHODS: LF prevalence data generated by the Nigeria Lymphatic Filariasis Control Programme during country-wide mapping surveys conducted between 2000 and 2013 were used to build the models. The dataset comprised of 1103 community-level surveys based on the detection of filarial antigenemia using rapid immunochromatographic card tests (ICT) and 184 prevalence surveys testing for the presence of microfilaria (Mf) in blood. Using a suite of climate and environmental continuous gridded variables and compiled site-level prevalence data, a quantile regression forest (QRF) model was fitted for both antigenemia and microfilaraemia LF prevalence. Model predictions were projected across a continuous 5 × 5 km gridded map of Nigeria. The number of individuals potentially infected by LF prior to MDA interventions was subsequently estimated. RESULTS: Maps presented predict a heterogeneous distribution of LF antigenemia and microfilaraemia in Nigeria. The North-Central, North-West, and South-East regions displayed the highest predicted LF seroprevalence, whereas predicted Mf prevalence was highest in the southern regions. Overall, 8.7 million and 3.3 million infections were predicted for ICT and Mf, respectively. CONCLUSIONS: QRF is a machine learning-based algorithm capable of handling high-dimensional data and fitting complex relationships between response and predictor variables. Our models provide a benchmark through which the progress of ongoing LF control efforts can be monitored.

The social, physical and economic impact of lymphedema and hydrocele: a matched cross-sectional study in rural Nigeria.

BACKGROUND: Lymphatic filariasis (LF) is a mosquito-borne parasitic disease and a major cause of disability worldwide. To effectively plan morbidity management programmes, it is important to estimate disease burden and evaluate the needs of patients. This study aimed to estimate patient numbers and characterise the physical, social and economic impact of LF in in rural Nigeria. METHODS: This is a matched cross-sectional study which identified lymphedema and hydrocele patients with the help of district health officers and community-directed distributors of mass drug administration programmes. A total of 52 cases were identified and matched to 52 apparently disease-free controls, selected from the same communities and matched by age and sex. Questionnaires and narrative interviews were used to characterise the physical, social and economic impact of lymphedema and hydrocele. RESULTS: Forty-eight cases with various stages of lower limb lymphedema, and 4 with hydrocele were identified. 40% of all cases reported feeling stigma and were 36 times (95% CI: 5.18-1564.69) more likely to avoid forms of social participation. Although most cases engaged in some form of income-generating activity, these were low paid employment, and on average cases spent significantly less time than controls working. The economic effects of lower income were exacerbated by increased healthcare spending, as cases were 86 times (95% CI: 17.48-874.90) more likely to spend over US $125 on their last healthcare payment. CONCLUSION: This study highlights the importance of patient-search as a means of estimating the burden of LF morbidity in rural settings. Findings from this work also confirm that LF causes considerable psychosocial and economic suffering, all of which adversely affect the mental health of patients. It is therefore important to incorporate mental health care as a major component of morbidity management programmes.

Environmental suitability for lymphatic filariasis in Nigeria.

BACKGROUND: Lymphatic filariasis (LF) is a mosquito-borne parasitic disease and a major cause of disability worldwide. It is one of the neglected tropical diseases identified by the World Health Organization for elimination as a public health problem by 2020. Maps displaying disease distribution are helpful tools to identify high-risk areas and target scarce control resources. METHODS: We used pre-intervention site-level occurrence data from 1192 survey sites collected during extensive mapping surveys by the Nigeria Ministry of Health. Using an ensemble of machine learning modelling algorithms (generalised boosted models and random forest), we mapped the ecological niche of LF at a spatial resolution of 1 km2. By overlaying gridded estimates of population density, we estimated the human population living in LF risk areas on a 100 × 100 m scale. RESULTS: Our maps demonstrate that there is a heterogeneous distribution of LF risk areas across Nigeria, with large portions of northern Nigeria having more environmentally suitable conditions for the occurrence of LF. Here we estimated that approximately 110 million individuals live in areas at risk of LF transmission. CONCLUSIONS: Machine learning and ensemble modelling are powerful tools to map disease risk and are known to yield more accurate predictive models with less uncertainty than single models. The resulting map provides a geographical framework to target control efforts and assess its potential impacts.