Effect of intra-urban temperature variation on tree flowering phenology, airborne pollen, and measurement error in epidemiological studies of allergenic pollen

AbstractAirborne allergenic pollen affects a significant part of the population and the information on pollen load is a valuable tool for public health prevention. The messages should be provided in a form easily understandable for the population. The study provides new insight for the categorisation of pollen load by defining thresholds solely from aerobiological data. Using the long-term airborne pollen data of Corylus, Alnus, Betula, Poaceae, and Artemisia have been evaluated the regionality of pollen concentrations in Lithuania. SPIn and peak values of the main pollen season highlighted as regionality indicators. The largest differences between stations were found in the cases of Corylus and Artemisia.The principle enabling a group of pollen concentrations into levels has been analysed based on retrospective aerobiological data of five pollen types. Thresholds were determined by employing the lowest peak value of the pollen season and applying the 25% principle for selected pollen types. The results were verified by performing associations of defined thresholds with retrospective morbidity data of allergic rhinitis and allergic asthma in Lithuania. Determined pollen thresholds can be used in epidemiological studies requiring associations with pollen concentration. Thresholds could also complement air quality information by integrating pollen load data into public messages or contribute to the development of mHealth systems.

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Neural networks for increased accuracy of allergenic pollen monitoring

Scientific Reports ◽

10.1038/s41598-021-90433-x ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Marcel Polling ◽

Chen Li ◽

Lu Cao ◽

Fons Verbeek ◽

Letty A. de Weger ◽

...

Keyword(s):

Neural Networks ◽

Airborne Pollen ◽

Pollen Grains ◽

Allergenic Pollen ◽

Herbarium Specimens ◽

Pollen Monitoring ◽

Pollen Concentrations ◽

Source Of Information ◽

Urticaceae Pollen

AbstractMonitoring of airborne pollen concentrations provides an important source of information for the globally increasing number of hay fever patients. Airborne pollen is traditionally counted under the microscope, but with the latest developments in image recognition methods, automating this process has become feasible. A challenge that persists, however, is that many pollen grains cannot be distinguished beyond the genus or family level using a microscope. Here, we assess the use of Convolutional Neural Networks (CNNs) to increase taxonomic accuracy for airborne pollen. As a case study we use the nettle family (Urticaceae), which contains two main genera (Urtica and Parietaria) common in European landscapes which pollen cannot be separated by trained specialists. While pollen from Urtica species has very low allergenic relevance, pollen from several species of Parietaria is severely allergenic. We collect pollen from both fresh as well as from herbarium specimens and use these without the often used acetolysis step to train the CNN model. The models show that unacetolyzed Urticaceae pollen grains can be distinguished with > 98% accuracy. We then apply our model on before unseen Urticaceae pollen collected from aerobiological samples and show that the genera can be confidently distinguished, despite the more challenging input images that are often overlain by debris. Our method can also be applied to other pollen families in the future and will thus help to make allergenic pollen monitoring more specific.

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The Effect of Random Error in Exposure Measurement upon the Shape of the Exposure Response

Dose-Response ◽

10.2203/dose-response.003.04.002 ◽

2005 ◽

Vol 3 (4) ◽

pp. dose-response.0 ◽

Cited By ~ 18

Author(s):

Kenny S. Crump

Keyword(s):

Measurement Error ◽

Measurement Errors ◽

Epidemiological Data ◽

Epidemiological Studies ◽

Random Errors ◽

Exposure Measurement ◽

Considerable Uncertainty ◽

Exposure Response ◽

Log Normal ◽

Normally Distributed

Although statistical analyses of epidemiological data usually treat the exposure variable as being known without error, estimated exposures in epidemiological studies often involve considerable uncertainty. This paper investigates the theoretical effect of random errors in exposure measurement upon the observed shape of the exposure response. The model utilized assumes that true exposures are log-normally distributed, and multiplicative measurement errors are also log-normally distributed and independent of the true exposures. Under these conditions it is shown that whenever the true exposure response is proportional to exposure to a power r, the observed exposure response is proportional to exposure to a power K, where K < r. This implies that the observed exposure response exaggerates risk, and by arbitrarily large amounts, at sufficiently small exposures. It also follows that a truly linear exposure response will appear to be supra-linear—i.e., a linear function of exposure raised to the K-th power, where K is less than 1.0. These conclusions hold generally under the stated log-normal assumptions whenever there is any amount of measurement error, including, in particular, when the measurement error is unbiased either in the natural or log scales. Equations are provided that express the observed exposure response in terms of the parameters of the underlying log-normal distribution. A limited investigation suggests that these conclusions do not depend upon the log-normal assumptions, but hold more widely. Because of this problem, in addition to other problems in exposure measurement, shapes of exposure responses derived empirically from epidemiological data should be treated very cautiously. In particular, one should be cautious in concluding that the true exposure response is supra-linear on the basis of an observed supra-linear form.

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Evaluating the power of the causal impact method in observational studies of HCV treatment as prevention

Statistical Communications in Infectious Diseases ◽

10.1515/scid-2020-0005 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Pantelis Samartsidis ◽

Natasha N. Martin ◽

Victor De Gruttola ◽

Frank De Vocht ◽

Sharon Hutchinson ◽

...

Keyword(s):

Time Series ◽

Measurement Error ◽

Time Series Data ◽

Temporal Trends ◽

Epidemiological Studies ◽

Series Data ◽

Treatment As Prevention ◽

Open Problems ◽

Multiple Characteristics ◽

Causal Impact

Abstract Objectives The causal impact method (CIM) was recently introduced for evaluation of binary interventions using observational time-series data. The CIM is appealing for practical use as it can adjust for temporal trends and account for the potential of unobserved confounding. However, the method was initially developed for applications involving large datasets and hence its potential in small epidemiological studies is still unclear. Further, the effects that measurement error can have on the performance of the CIM have not been studied yet. The objective of this work is to investigate both of these open problems. Methods Motivated by an existing dataset of HCV surveillance in the UK, we perform simulation experiments to investigate the effect of several characteristics of the data on the performance of the CIM. Further, we quantify the effects of measurement error on the performance of the CIM and extend the method to deal with this problem. Results We identify multiple characteristics of the data that affect the ability of the CIM to detect an intervention effect including the length of time-series, the variability of the outcome and the degree of correlation between the outcome of the treated unit and the outcomes of controls. We show that measurement error can introduce biases in the estimated intervention effects and heavily reduce the power of the CIM. Using an extended CIM, some of these adverse effects can be mitigated. Conclusions The CIM can provide satisfactory power in public health interventions. The method may provide misleading results in the presence of measurement error.

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The late flowering of invasive species contributes to the increase of Artemisia allergenic pollen in autumn: an analysis of 25 years of aerobiological data (1995–2019) in Trentino-Alto Adige (Northern Italy)

Aerobiologia ◽

10.1007/s10453-020-09663-7 ◽

2020 ◽

Vol 36 (4) ◽

pp. 669-682 ◽

Cited By ~ 1

Author(s):

Antonella Cristofori ◽

Edith Bucher ◽

Michele Rossi ◽

Fabiana Cristofolini ◽

Veronika Kofler ◽

...

Keyword(s):

Invasive Species ◽

Pollen Season ◽

Airborne Pollen ◽

Pollen Grains ◽

Late Summer ◽

Natura 2000 ◽

Allergenic Pollen ◽

Pollen Concentration ◽

Pollen Concentrations ◽

Negative Impacts

AbstractArtemisia pollen is an important aeroallergen in late summer, especially in central and eastern Europe where distinct anemophilous Artemisia spp. produce high amounts of pollen grains. The study aims at: (i) analyzing the temporal pattern of and changes in the Artemisia spp. pollen season; (ii) identifying the Artemisia species responsible for the local airborne pollen load.Daily pollen concentration of Artemisia spp. was analyzed at two sites (BZ and SM) in Trentino-Alto Adige, North Italy, from 1995 to 2019.The analysis of airborne Artemisia pollen concentrations evidences the presence of a bimodal curve, with two peaks, in August and September, respectively. The magnitude of peak concentrations varies across the studied time span for both sites: the maximum concentration at the September peak increases significantly for both the BZ (p < 0.05) and SM (p < 0.001) site. The first peak in the pollen calendar is attributable to native Artemisia species, with A. vulgaris as the most abundant; the second peak is mostly represented by the invasive species A. annua and A. verlotiorum (in constant proportion along the years), which are causing a considerable increase in pollen concentration in the late pollen season in recent years.. The spread of these species can affect human health, increasing the length and severity of allergenic pollen exposure in autumn, as well as plant biodiversity in both natural and cultivated areas, with negative impacts on, e.g., Natura 2000 protected sites and crops.

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Seasonal pollen distribution in the atmosphere of Hobart, Tasmania: preliminary observations and congruence with flowering phenology

Australian Journal of Botany ◽

10.1071/bt10095 ◽

2010 ◽

Vol 58 (6) ◽

pp. 440 ◽

Cited By ~ 8

Author(s):

D. Y. P. Tng ◽

F. Hopf ◽

S. G. Haberle ◽

D. M. J. S. Bowman

Keyword(s):

Native Plants ◽

Airborne Pollen ◽

Flowering Phenology ◽

Sampling Location ◽

Minor Role ◽

Sampling Effort ◽

Pollen Load ◽

Flowering Duration ◽

Pollen Types ◽

Atmospheric Pollen

The atmospheric pollen loads of Hobart, Tasmania, Australia, were monitored between September 2007 and July 2009. To examine the match of the airborne pollen composition with the flowering duration of their contributing plants, the phenology of native and non-native plants in various habitats near the pollen-trapping site was undertaken between August 2008 and July 2009. The pollen load was found to have a strong seasonal component associated with the start of spring in September. This is incongruent with the peak flowering season of the total taxa in October. In most taxa, atmospheric pollen signatures appeared before flowering was observed in the field. The presence of most pollen types in the atmosphere also exceeded the observed flowering duration of potential pollen-source taxa. Reasons for this may be related to the sampling effort of phenological monitoring, pollen blown in from earlier flowering populations outside of the sampling area, the ability of pollen to be reworked, and the large pollen production of some wind-pollinated taxa. In 2007–2008, 15 pollen types dominated the atmosphere, accounting for 90% of the airborne pollen load. The top six pollen types belonged to Betula, Cupressaceae, Myrtaceae, Salix, Poaceae and Ulmus. Comparatively, the annual pollen load of Hobart is lower than in most other Australian cities; however, the pollen signal of Betula is inordinately high. Native plants play a minor role as pollen contributors, despite the proximity of native habitats to the pollen-sampling location. The implications of the aerobiological observations are discussed in relation to public health.

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Comparative Study of Airborne Pollen from the Northern to the Southern of Tunisia

Asian Journal of Biology ◽

10.9734/ajob/2019/v8i330063 ◽

2019 ◽

pp. 1-8 ◽

Cited By ~ 1

Author(s):

S. Hadj Hamda ◽

A. Ben Dhiab ◽

M. Msallem ◽

A. Larbi

Keyword(s):

Crop Production ◽

Airborne Pollen ◽

Flowering Phenology ◽

Plant Distribution ◽

The South ◽

Pollen Type ◽

The North ◽

Flowering Season ◽

Pollen Types ◽

Study Sites

Aerobiology is a multidisciplinary science dealing with biological particles in the atmosphere generated by natural activities during flowering season. Airborne pollen is now the main studied biological structure which is used as a reliable tool to study plant phenology, plant distribution changes and prediction of crop production. The main aims of this work is to determine the distribution of the different spring flowering species from the North to the South of Tunisia and to establish the pollen spectrum of three regions Mornag (North), Menzel M’hiri (Centre) and Chaal (South) in 2017. Airborne pollen data were collected using three volumetric Hirst-type spore traps placed in Mornag (36°39N; 10°16E), Menzel M’hiri (35°38N; 10°41E) and Chaal (34°34N; 10°19E) during olive flowering season. The highest pollen index was recorded in the north (Mornag, 6487.1) corresponding mainly to 18 different pollen types emitted by anemophilous species with an important presence of Cupressus pollen type having the highest contribution. Lower pollen amounts were recorded in Menzel M’hiri (5983.8) and Chaal (925.3). Olea eurpoeae was the most presented pollen type in these regions. However comparing the different study sites we can note a large distribution of some taxa from north to the south. The main common taxa were Olea europaea, Cupressaceae, Poaceae and Amaranhaceae. Their atmospheric concentrations varied also between the regions. Individual pollen index showed a sharp heterogeneity between the taxa in the same region in one hand and between the study sites in the other hand, thus a statistical analysis was performed to define the main group of taxa according to their individual pollen index. Flowering phenology of the main common taxa was also established.

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