The Mosquito Protocol Bundle

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I. Summary

Pathogens spread by mosquitos kill more than a million people a year across the world, mostly in tropical regions. Increasing temperature and rainfall are potentially providing suitable conditions and habitats for mosquitos to spread pathogens, however, climate alone is not enough. The mosquito has already hitchhiked to Europe and North America with eggs attached to used tires and lucky bamboo. Movement of people, not shifts in climate is the biggest risk. This is why doing the GLOBE Mosquito Habitat Mapper App along with GLOBE Hydrology and Atmosphere protocols is important for raising awareness, pathogen management and control in your area. This protocol bundle combines all GLOBE protocols that are related to the Mosquito habitat mapper app and explains how they are related. You can make a difference in tracking and controlling the spread of mosquitos and help save your loved ones from getting dengue, Zika and other illnesses.

 

II. List of the GLOBE Protocols included in this bundle

Hydrology Protocols

Water temperature

Water pH

Turbidity

Salinity

Dissolved oxygen

Atmosphere Protocols

Air temperature

Rainfall

Rain pH

Relative humidity

 

III. Science Background

Concerns regarding the impact of global warming on vector-borne diseases, have intensified interest in the relationship between temperature and dengue fever and Zika incidences and include a focus on determining whether climatic factors alone can be used to indicate or predict variations in dengue and Zika incidences. However, even if epidemiological surveys show that in endemic situations trends in incidence are generally driven by variations in seasonal climate, these changes in incidence depend on many parameters and the impact of temperature alone cannot be isolated easily from that of other climatic factors (e.g., rainfall, relative humidity).

 

In the last 50 years, there has been a thirtyfold increase in mosquito-borne diseases as well as geographical expansion of incidences to new areas and countries, particularly in rapidly expanding urban and semi-urban places in middle- and low-income countries where water storage and waste disposal services are limited. An estimated 50 million dengue infections occur annually and about 2.5 billion people live in regions with the potential risk of dengue transmission.

 

Global climate change poses the threat of serious social upheaval, population displacement, economic hardships, and environmental degradation. Human health could be influenced by increased variability and sustained climate changes. The ecology, development, behavior and survival of mosquitoes and the transmission dynamics of the diseases they transmit are strongly influenced by climatic factors (i.e., precipitation, temperature, relative humidity, wind, storm severity, frequency of flooding or droughts and rising sea levels). Changes in temperature, rainfall and relative humidity have potential to enhance vector development, reproductive and biting rates, shorten pathogen incubation period and encourage adult longevity. In addition, changes in wind direction, velocity and frequency will have an impact on adult mosquito populations, affecting dispersal, survival and aspects of the general behavior of many species. The complex interplay of all these factors determines the overall effect of climate on the local prevalence of mosquito-borne diseases.

 

The Mosquito Bundling provides a group of GLOBE protocols through which knowledge can be integrated to enable students and scientists gain a better understanding regarding dengue fever and zika prevention and control.

 

IV. Discussion of GLOBE Protocol included in the bundle

Indoor/outdoor containers. Students can compare the number of mosquito larvae in indoor and outdoor containers, the number of positive containers that mosquito species found indoors versus outdoors? Would water pH, temperature, and turbidity in indoor and outdoor containers differ? Would some mosquito larvae specie be more abundant in water with lower pH than with higher pH?

Containers with lids and without lids. Some houses put lids to cover their water containers. It would be interesting to show that mosquito larvae were higher in containers without lids than with lids. GLOBE students can demonstrate this to your local community to raise community awareness.

Dark/light containers. Is it a myth that mosquitos prefer darker cloths, darker corners of the house? GLOBE students can prove this by showing water container colors and dark/light have some effect on mosquito females when they choose to lay their eggs

Earthen/Plastic containers and Natural/artificial containers. Urbanization is a global phenomenon and we have to admit that plastic containers come with urbanization. GLOBE students could monitor how people in their area have changed from using earthen and natural materials to plastics. You would be surprised that mosquitos also have changed their habit and preferences by laying eggs more in plastic containers than earthen jars. GLOBE students can check if mosquito females in their area have changed their habit and prefer to lay eggs in plastic containers .

Atmospheric factors. The GLOBE Program provides several atmospheric measurements (e.g., temperature, humidity, rainfall, rainy days, cloud type and cloud cover). Several studies have shown that monthly max/min/mean temperature, min/mean relative humidity, max/mean wind speed, monthly rainfall, daily max rainfall, rainy days, cloudiness, and visibility were positively associated with monthly

 

V. Example of case studies

Case study I: The effect of ENSO on dengue cases in Muang Nakhon Si Thammarat by Princess Chulabhorn Science High School Thammarat, Thailand

 

Research Questions: How do the El Niño and La Niña events influence dengue cases in Muang district, Nakhon Si Thammarat, southern Thailand?

 

Introduction

Dengue cases in Muang Nakhon Si Thammarat in the wet season were higher than in the dry season (Figure 1) (Noradin et al., GLOBE IVSS 2016)

Figure 1. Monthly dengue cases in wet and dry seasons at Muang Nakhon Si Thammarat, Thailand for January 2011-January 2016 (Noradin et al., 2016).

 

Data Collection

Dengue cases in January 2011-December 2017 were obtained from the Vector-Borne Disease Control Centre laboratory 11. Nakhon Si Thammarat atmospheric data were collected from Meteorological Department of Thailand during January 1987-December 2017. Nakhon Si Thammarat atmospheric data were collected from the automatic weather station located at Princess Chulabhorn College Nakhon Si Thammarat during January 2017-December 2017.

El Niño-La Niña data were obtained from the National Weather Service Climate Prediction Center during 1987-2017. We collected daily rainfall, rainy days, relative humidity, mean/min/max temperature and El Niño -La Niña data. We collected daily rainfall, rainy days, relative humidity, mean/min/max temperature and El Nino-La Nina data. We separated dengue cases from January 2011- December 2017 into year of El Nino-La Nina and normal year. Sea Surface Temperature (SST) data during January 1987 to December 2017 were obtained from http://www.cpc.ncep.noaa.gov/data/indices/sstoi .indices. We collected SST data using data from Nino 3.4 index. This information indicates the state and severity of SST at each time period and indicate the starting point of El Niño and La Niña events (Xue et al., 2003).

 

Data analysis

House index was calculated as the number of positive households divided by the total number of households inspected. Household locations with the number of mosquito larvae were visualised as the point overlaid on Google Earth. Descriptive statistics were calculated. Independent sampled t-tests were used to test the mean differences of dengue cases and climatic factors are influenced by El Niño-La Niña events. Pearson correlations were used to test the association between dengue cases and climatic factors. The significant tests were one-tailed with significant level at P<0.05.

 

Results

Number of Dengue cases and local Temperature Index

The ENSO indices used in this study were the Nino 3.4 during 1987–2017. ENSO events were defined as periods at or above the +0.5°C SST anomaly for warm (El Niño) events and at or below the -0.5°C anomaly for cold (La Niña) events. Our results showed that La Niña events were observed in 2011–2012, normal events were observed in 2013–2014, and El Niño events were observed in 2015–2016 (Figure 2).

Figure 2. Dengue cases in Muang Nakhon Si Thammarat (blue bars represent monthly dengue cases) and ENSO indices (orange line represents Nino 3.4 Index).

 

The number of dengue cases seems to be increasing after El Niño events (Figure 3).

Figure 3. The Dengue incidences in El Niño (green bars), Normal (blue bars) and La Niña (yellow bars) events.

 

The ENSO index and Relative Humidity in El Niño times.

Relative humidity (%) was positively correlated with Nino3.4 in the Muang district, Nakhon Si Thammarat province during El Niño events. Climate factors were not significantly correlated with Nino 3.4 in La Niña events (Table 1).

 

Table 1: Spearman Correlation coefficient of Nino 3.4 and El Niño’s climatic factors (N=32)

 

  Rainfall (mm) Rainy days (days) Mean Temperature (°C) Relative Humidity (%)
El Niño event        
Spearman Correlation 0.146 0.329 -0.221 0.550
Sig (1-tailed) 0.258 0.067 0.161 0.004
La Niña event        
Spearman Correlation 0.190 -0.289 0.365 -0.303
Sig (1-tailed) 0.211 0.108 0.057

0.097

 

Climatic factors and dengue cases during El Niño events

Rainfall, rainy days, mean temperature and relative humidity were positively correlated with dengue cases in Muang district, Nakhon Si Thammarat in El Niño and La Niña events. The number of rainy days was the only factor that positively correlated with dengue cases. Other climatic factors were not significantly correlated with dengue cases (Table 2).

 

Table 2: Spearman Correlation coefficient of dengue cases and El Niño’s climatic factors (N=32)

 

  Rainfall (mm) Rainy days (days) Mean Temperature (°C) Relative Humidity (%)
El Niño event        
Spearman Correlation 0.454 0.485 -0.647 0.581
Sig (1-tailed) 0.017 0.016 0.002 0.002
La Niña event        
Spearman Correlation 0.294 -0.409 0.037 -0.067
Sig (1-tailed) 0.104 0.037 0.439

0.389

 

 

Table 3: Number of household, positive households, house index and dengue cases during El Niño - El Niño events.

 

  Aedes Larvae
  Mar-2016 (El Niño event) Jan-2018 (La Niña event)
No. of households 32 32
No. of positive households 25 23
House Index (HI) (%) 78.13 72.88

 

 

House index at Muang Nakhon Si Thammarat and El Niño - La Niña events.

From the GLOBE mosquito larvae collection in March 2016 (El Niño event) and February 2018 (La Niña event), house indices (HI) for Ae. aegypti and Ae. albopictus were extremely high (Table 3). Nakhon Si Thammarat province had the HI >5% during El Niño events in March 2016 (HI 78.13%) and La Niña events in January 2018 (HI 72.88%) indicates that Nakhon Si Thammarat is a dengue high risk area.

 

VI. Summary

The prevalence of mosquito borne diseases is expected to increase across the world as temperatures increase. This could mean higher rates of dengue, Zika, malaria and other illnesses. Doing the GLOBE Mosquito Habitat Mapper App helps us gain a better understanding on when and where mosquitos present in your area in what numbers. With other GLOBE Hydrology and Atmosphere protocols, this would help us understand the arrival of rainy season, the higher average temperature and high humidity which mean a longer mosquito breeding season and more vulnerability for humans. It is time for you to stand up and do the GLOBE for a better community in which you live.