Nghiên cứu đặc điểm khí hậu tương quan tới sốt xuất huyết dengue tại 7 tỉnh ven biển nam bộ và hiệu quả diệt bọ gậy muỗi aedes của ABATE 1SG tt tiếng anh

MINISTRY OF EDUCATION
AND TRAINING

MINISTRY OF NATIONAL
DEFENCE

VIETNAM MILITARY MEDICAL UNIVERSITY

BUI KHANH TOAN

STUDY ON CORRELATION BETWEEN CLIMATE FEATURES
AND DENGUE IN 7 COASTAL PROVINCES OF SOUTHERN
VIETNAM AND EFFECTIVENESS OF ABATE 1SG
LARVICIDE AGAINST AEDES LARVAE

Speciality: Health management.
Code: 9720801.

SUMMARY OF PhD THESIS

HANOI - 2019


A DISSERTATION COMPLETED IN VIETNAM MILITARY
MEDICAL UNIVERSITY
Advisors:
1. Nguyen Huy Nga, Ass. Prof., PhD.
2. Nguyen Xuan Truong, PhD.
Committee member 1: Nguyen Thi Thuy Duong, Ass. Prof., PhD.
Committee member 2: Nguyen Khac Luc, Ass. Prof., PhD.
Committee member 3: Truong Viet Dung, Prof., PhD.

The dissertation will be defended by a thesis committee council in
Vietnam Military Medical University
At: hour date month year
The thesis can be found at:
1. National Library
2. Military Medical University Library


1

INTRODUCTION
Vietnam is one of the world’s most vulnerable countries to climate change
and sea level rising. Climate change has a devastating effect on ecosystem,
and one of its outcome is a range of factors which predispose to environment
and health, leading to not only outbreaks of major epidemics but also
obscure diseases. Dengue hemorrhagic fever is an infectious disease that has
been linked to climate change trends.
Of all regions in Vietnam, Southern coast has been significantly affected by
extreme weather and climate change. The incidence of dengue in this area
has seen an unusual fluctuation. There has been a sudden change in the
frequency and characteristics of dengue fever, which obstructs disease
prevention in the Southern provinces. Therefore, the study of features of
climate and their relationship with dengue fever is necessary. Its result will
help to analyze new attributes of dengue epidemic from which to come up
with optimal solutions to control and prevent it in this region.
1. Research objectives:
1. To describe the characteristics of climate and analyze its correlation
with the incidence of dengue fever in 7 Southern coastal provinces
in the period of 2003-2013.
2. To assess the effectiveness of ABATE 1SG larvicide - an

intervention to kill Aedes larvae in dengue prevention and control in
Rach Gia city, Kien Giang province.
2. New contributions of the thesis
- The study indicated frequency of Dengue disease in coastal
provinces of Southern Vietnam in the period of 2003-2013. The disease
appears all the year round; the frequency of the disease is lowest in February,
March, April and increases gradually from May, reaches at peak in rainfall
months: July, August, September and October.
- The study shows that there is a clear relationship between the
number of Dengue cases and climate features in the region. The correlation
between the number of Dengue cases correlates and temperature is close and
positive with a lag of 1 month, 2 and 3 months earlier (lag = -3, -2, -1); the
closest correlation is at lag of 3 months earlier. The correlations between the
number of Dengue cases and both rainfall and humidity are high and
positive, with a lag of 1 month and 2 months earlier (lag = -2, -1).


2

- The study proved that ABATE 1SG kills effectively Aedes larvae
in outdoor water storage containers. The results of the intervention show that
the effectiveness of Abate 1SG larvicide is 100% after 24 hours; 100% after
1 month; and maintains a high efficiency after 3 months (98.68%) even in
the outdoor condition of the water storage containers whose the levels are
often changed due to the weather.
3. Outline: The thesis includes 115 pages and 4 chapters:
Introduction: 02 pages
Chapter 1. Literature review: 33 pages
Chapter 2. Research subjects and methods: 20 pages
Chapter 3. Research results: 33 pages

Chapter 4. Discussion: 25 pages
Conclusion: 01 page
Recommendation: 01 page
References: 105 documents (45 Vietnamese papers, 60 English papers).
CHAPTER 1
LITERATURE REVIEW
1.1. Climate change in Viet Nam
Statistics of rainfall over Vietnam has shown a significant increasing trend
in the southern region while it has tended to decrease in the northern region.
In average for the whole country, the annual rainfall decreased 2% in the
period of 50 years (1958-2007). Average annual temperatures in the coastal
zones of Vietnam have increased significantly, from 0.5 to 0.7 oC.
1.2. The characteristics of 7 Southern coastal provinces
Seven southern coastal provinces in the study include Kien Giang, Ca Mau,
Bac Lieu, Soc Trang, Tra Vinh, Ben Tre, and Tien Giang. They are coastal
provinces in Southwestern region, is also known as the Western Region or
Nine Dragon river delta. Today, the region comprises 13 provinces/cities.
Southwestern Region is a part of Mekong Delta River with the area of
40818.3 km2, the population of 17.7 million and its population density is
435people/km2.
A lot of researches have shown that Southwestern provinces are at risk
flooding. Our country will lose 38.9% of the total area of the Mekong Delta


3

– the biggest rice granary of the country if the sea level rises 100cm by the
end of the century. Localities of Hau Giang, Kien Giang, and Ca Mau are
expected to suffer the most with inundated areas up to 80.62%, 80.62% and
57.69% respectively.

1.3. Dengue fever and the effects of climate change on Dengue
Dengue is a mosquito-borne viral disease widely spread in tropical and
subtropical regions. It is a severe disease transmitted by day-biting midges. It
is estimated that 3.5 billion are at risk of infection with dengue viruses - 55%
of the world's population.
The dengue virus transmission occurs from the bite of an infected Aedes
mosquitoes. Mosquitoes first become infected with dengue virus by feeding
on the blood of a dengue-infected person and are often found in and around
human dwellings.
The cases of dengue tend to increase in recent years. Official statistics have
shown that in 2008 there were 96,451 cases of dengue, and it rose to 105,370
in 2009 and in 2010 about 128,831 people suffered from dengue fever.
Temperature is said to affect each stage of the mosquito's life cycle.With too
high or too low temperatures in the favorable survival range of Ae. aegypti,
egg laying time increases, causing a decrease in egg number. Eggs hatch into
larvae which continue their development to become pupae. It is abundant in
tropical regions, where environmental factors (e.g., rainfall, temperature, and
humidity) and human factors (crowding population, poor hygiene) favor its
life cycle.
Monitoring is a key component of any prevention programs and control of
dengue fever because it provides the necessary information for risk
assessment, response and program evaluations. Supervisors can apply active
or passive data collection process.
Vector surveillance is used to identify the main source of reproduction of
mosquitoes transmitting diseases, vector susceptibility to chemical
insecticides and evaluate vector control in the community.
Chemical measures are used to control mosquitoes that spread dengue virus
in dengue outbreaks, e.g. by using ABATE 1SG in water storage containers,
ultra-low volume and indoor residual spraying. The use of insecticides to
direct against adult mosquitoes has been proved to be able stamp out

epidemics in many countries around the world.


4

ABATE 1SG (transaction name ABATE 1SG) is a phosphate compound
widely used in the world to kill mosquitoes that spread dengue, Japanese
encephalitis, malaria ... ABATE 1SG is recommended by WHO because it
helps to kill mosquito larvae in public health programs, and can be used for
both drinking water storage containers but at doses not exceeding 1mg/litre.
CHAPTER 2
RESEARCH TARGETS AND METHODS
2.1. Research target, time and place
2.1.1. Research targets
* Descriptive study:
- Climate features in 7 southern coastal provinces including temperature,
humidity, rainfall by month in the period of 2003-2013.
- Reported cases and deaths of dengue in 7 southern coastal provinces.
- Vector of dengue transmission including larvae and mosquito indices by
month in Kien Giang province in the period of 2011-2013.
* Intervention study:
- Households and water storage containers in An Hoa and An Binh wards in
Rach Gia city, Kien Giang province.
2.1.2. Research place
- Descriptive study: 7 southern coastal provinces are the areas most affected
by climate change, including: Tien Giang, Ben Tre, Tra Vinh, Soc Trang, Bac
Lieu, Ca Mau and Kien Giang.
- Intervention study: An Hoa ward (intervention group) and An Binh ward
(control group) in Rach Gia city, Kien Giang province.
2.1.3. Research time

The study was conducted within 30 months, divided into 2 stages:
- Stage 1: studying climate features correlation with dengue: 20 months.
- Stage 2: develop and implement intervention in the field in dengue
prevention and control: 10 months.
2.2. Research design
Research in the community to describe climate features climate features
correlation with dengue, set up intervention models in the community,
including 2 studies:


5

- Descriptive cross-sectional studies: research on climate features correlation
with dengue in 7 southern coastal provinces.
- Intervention study: Develop and implement intervention in the field in
dengue prevention and control in Rach Gia city, Kien Giang province.
2.3. Content and methods of data collection
2.3.1. Research on climate features in the coastal areas of the southern
region in the period of 2003-2013
Retrospective parameters include:
- Air temperature (oC): Monthly average temperature.
+ Monthly average temperature = Total average temperature each day in the
month/total number of days in the month.
- Air humidity (relative humidity - %): Monthly average humidity.
- Rainfall (mm): monthly rainfall.
2.3.2. Research on climate features and their correlations with dengue in
7 coastal provinces in the Southern Vietnam
2.3.2.1. Characteristics of dengue in 7 southern coastal provinces
Retrospective secondary data based on data on dengue epidemics reported by
the health system in the period of 2003-2013.

Retrospective parameters include dengue cases and deaths: number of cases
and deaths of dengue by month.
* Research variables and indexes:
Order Variables name
Collecting methods
1
Time
Calculating each period by 1 month
(2003 - 2013)
2
Number of cases and
Retrospective
deaths of dengue by
month
3
Average number of
Calculated by the average of the number
cases and deaths of
of dengue cases and deaths by month
dengue by month from from 2003-2013
2003-2013
2.3.2.2. Describe the correlation between climate features and dengue:
Correlation analysis (Autocorrelation): Correlation refers to the temporal
correlation between past and future values of an object and phenomenon.


6

2.3.2.3. Describe the correlation between climate features and vector of
dengue transmission in Kien Giang:

 Select research location:
Kien Giang is a place that meets the study’s condition and has been
selected for the study
 Time: from 2011 - 2013.
 Investigate, collect larvae and mosquitoes
+ Investigate and collect larvae
Investigating and catching larvae place
+ Techniques: Use a flashlight on the water containers and use the racket
to remove the larva. Turn over the tray containing water available to catch.
Use a straw to suck the larvae into the jar. Investigation of larvae in tree
niches, stone niches is difficult to use a racket, use the straw that has a long
pipette bulb instead. Absorb water from the niche, pour it into the enamel
tray to find.
 Identify mosquitoes’ distribution:
Indicators for assessment of Aedes mosquito larvae
+ House Index (percentage of houses infested with mosquito larvae or
pupae): HI (%)
+ Container Index (percentage of water-holding containers infested with
larvae or pupae): CI (%)
+Breteau index (BI): number of positive containers per 100 houses
inspected.
+ Pupa index (PI): number of pupae per house inspected.
+ Mosquito density index: number of mosquitoes per house
+ Mosquito house index: percentage of house infested with mosquito
 Study the correlation between climate features and distribution of
dengue vector
We have a chronological sequence (x 1, x2, ..., xn) with xi representing the data
at time i. The Mann-Kendall (S) statistical value is defined
S = sign(xj - xk) = 1 if xj>xk(j=k+1)
S = sign(xj - xk) = 0 if xj = xk(j=k+1)

S = sign(xj - xk) = -1 if xj

7

Assign r value:
r has a normal distribution of N (0,1), positive r values reflect the uptrend of
the chain, negative r values reflect the downward trend of the chain.In the
study, trend values are indicated with a 10% significance level (α = 0.1). In
the seasonal trend analysis (Seasonnal Mann - Kendall test) the value S =
sign (xj - xk) is calculated similarly but j = k + t with (t is the period of the
season to consider, in seasonal trend analysis, we choose t = 12).
Along with that we use the Sen’s slope, the Sen trend reflects the magnitude
of the chain trend, which is defined as the median of the sequence consisting
of n (n-1) / 2 elements.
if k = 1, 2, ..., n -1.
In the study, trend values will be reflected by the Sen trend indicator when
satisfying the 10% significance level.
2.3.4. Evaluation of the effectiveness of ABATE 1SG against Aedes
mosquito larvae in dengue prevention:
a. Target, location and time of the study:
* Study target:
- Water storage containers in residential clusters are perfect places Aedes
mosquito larvae to take up residence.
- Aedes mosquito larvae in An Binh and An Hoa wards in Rach Gia city.
- People living in households with application area of ABATE 1SG: 212
people.
* Criteria for selecting water storage containers for testing:
+ not used for drinking water.
+ not used for breeding useful aquatic or marine products.

+ not containing natural biological agents which are resistant to larvae, such
as mesocyclops.
+ water storage containers are uncovered containers.


8

+ water storage containers should be fairly fixed in terms of location and
storage volume, ensuring traceability throughout the study.
* Study location: The selected location are two wards in Rach Gia city, Kien
Giang province: An Hoa ward (intervention group) and An Binh ward
(control group). The communities in two wards have similar habitat
conditions.
* Study time: The study was conducted from April 2014 to November 2014.
+ From April to August 2014: Select study location and intervention
arrangement;
+ August 2014: Investigation before application and application of ABATE
1SG (1%);
+ August 2014: Investigation after 24 hours.
+ September 2014: Investigation after 1 month.
+ November 2014: Investigation 3 months after application.
b. Study content:
- Evaluation of indicators of water storage containers and Aedes mosquito
larvae in field research.
- Evaluate the effectiveness of ABATE 1SG in terms of killing larvae by
time: after 24 hours, after 1 month and 3 months.
- Evaluate the understanding and acceptance of the community about
ABATE 1SG use in killing Aedes mosquito larvae by interviewing 212
households in the experimental group.
c. Study’s methods and techniques:

Application of cross-sectional descriptive study design, sociological
investigation and design of community-based intervention research, pre-post
control and comparison groups.
* Sample size and sampling method:
- Sample units are water storage containers regardless of types and volumes.
- Sample size is calculated by the formula for the sample size of the
intervention study:
n=
q = 1-p
F = (Z/2 + Zβ)2

among them

p=


9

D = [p1 - p2]
n: Number of water storage containers applied in the study.
p: Container index (CI).
p1: The rate before intervention (approx. 80%).
p2: The rate after intervention, is expected to be 10%.
With a confidence interval is 95% and a sample effect is 95%, the minimum
sample size of each group is 200. During the evaluation process, the water
containers were easy to change due to the relatively long evaluation time,
therefore we investigated 348 water containers. In addition to ensuring the
assessment of indicators of larvae sources, the minimum number of
households to be surveyed is 200 households for each group. In fact, we
investigated 212 households in each group.

To determine the source of larvae, it is necessary to count the number of
larvae Aedes in water storage containers, then determine the source of Aedes
mosquitoes larvae by calculating the infection and concentration ratio of
larvae in each type of water container by the following formula:
Number of Aedes larvae captured in
each type of water container
Concentration ratio of =
larvae
(%)

x 100
Total number of Aedes larvae caught
during the investigation

Infection rate: Percentage of water containers with larvae/number of Ae.
Aegypti or Ae. Albopictus larvae.
- Indicators for larvae
House Index (percentage of houses infested with Aedes larvae): HI (%)
Numbers of houses infested with Aedes larvae
HI (%) =
x 100
Total number of houses investigated
Container index (CI): Percentage of water containers with Aedes larvae
Total number of water containers infested with
Aedes larvae
CI (%) =
x 100
Total number of water containers investigated
Breteau Index (BI): Number of water containers infested with Aedes larvae
in 100 houses investigated. For practical use BI is calculated as follows:

10

Total number of water containers infested with Aedes
=
larvae
BI
x 100
Total number of houses investigated
*Materials and techniques:
- Chemicals and dosage for test:
+ 1% ABATE 1SG chemical, product name: ABATE 1SG
+ Dosage: 1g ABATE 1SG 1% / 10 liters of water.
+ ABATE 1SG 1% is packed in plastic jars weighing 100g.
- Field research method:
In the residential area of An Hoa Ward, Rach Gia city: 212 households with
water storage containers were used to test ABATE 1SG 1% and selected 212
other households in An Binh Ward with the same living conditions as 212
households of the intervention group to control.
Investigating all water storage containers, in particular the intervention group
was 348 water storage containers, the control group was 345 ones.
Interventional water storage containers with ABATE 1SG and noninterventional water storage containers are distinctively marked.
Before experiment, all water storage containers were checked and recorded
the rich presence of Aedes larvae, then the water storage containers in the
intervention group would be applied ABATE 1SG at 1g dose ABATE 1SG
1%/10 liters of water. The evaluation of larvae indexes for all groups for the
first time was done after 24 hours, the following evaluation was conducted
after 1 month and 3 months.
* The method of data collection:

+ The investigation process of Aedes larvae in the field was recorded
according to routine insect investigation of the National Institute of Hygiene
and Epidemiology.
+ Beetles collected will be species-calculated in Kien Giang Preventive
Medical Center.
+ Use questionnaires to assess the attitudes, needs, preferences and
effectiveness of ABATE 1SG.
+ Participating in the survey of water storage containers and larvae are
officials with entomological expertise in Kien Giang Preventive Medical
Center.


11

+ Participating in interviewing subjects in the pilot area are officials of the
Department of Infectious Disease Control and Vaccine - Kien Giang
Preventive Medical Center.
*Methods of processing data, controlling errors:
The indicators evaluated include:
Indicators of larvae: Concentration rate, infection rate; CI, HI, BI, Larvae
Density Index.
The efficiency index (EI):
EI =

x 100

p1 = CI before application.
P2 = CI after application
2.4. Error and controlling errors
Errors in the study may include errors due to the original data set

and errors due to data entry and data processing.
The original data set may be systematic errors due to the fact that the
total number of cases reported in the health system do not fully reflect but
reflect only a fraction of the total number of actual cases in the community
within a certain period of time .
Errors in data entry were overcome by designing a set of data
collection tools from the epidemic data set, double data entry, cleaning,
checking pre-analysis data to reduce errors due to data entry process.
CHAPTER 3
RESEARCH RESULTS
3.1 CLIMATE FEATURES OF SOUTHERN COASTAL REGION IN
THE PERIOD OF 2003-2013
The climate in Southern costal provinces is tropical, hot and humid. There
are two main seasons: rainy season and sunny season.


12

Figure 3.1. Monthly average temperature variation at the Southern coast
stations in the period of 2003-2013
The annual average temperature of the region is 26-27 ° C, with an average
temperature variation of 3 - 3.5°C.
Humidity:

Figure 3.2. Variation of monthly average humidity at Southern coast stations
in the period of 2003-2013
Average relative humidity for many years is 82 - 83%. The lowest average
humidity is in February and March, about 77-82%, the highest is August,
September and October, varying around 85-89%.
Rain:

Rainfall in the Mekong Delta is quite large, averaging 1,400 - 2,200
mm/year. The province with the lowest rainfall is Tien Giang (1,500
mm/year), the province with the highest rainfall is Ca Mau (2,200 mm/year).


13

Figure 3.3. Variation of monthly average rainfall at Southern coast stations
in the period of 2003-2013
Rainfall recorded at least in the plain is Go Cong (Tien Giang) with only
1,200 mm / year, on average there are 100 - 110 rainy days / year. Phu Quoc
Island (Kien Giang) is considered to have the highest rainfall in the delta:
3,145 mm with an average of 140 rainy days / year.Months with the least
rainy days are December to March, varying from 0 to 6 rainy days per
month. The months with the highest rainy days are from May to October,
varying from 13 to 21 rainy days per month.
3.2. THE CORRELATION BETWEEN CLIMATE AND DENGUE IN
THE SOUTHERN COASTAL REGION:
3.2.1. Dengue fever in the Southern coastal region in the period of 20032013:

Figure 3.4. Incidents of dengue and death of dengue in the Southwest coastal
region in the period of 2003 – 2013
In 2007, in the Southern coastal region, the number of dengue cases was
35,055 cases. Provinces with increased number of haemorrhagic fever cases


14

compared with 2006 were Bac Lieu, Ben Tre, Ca Mau, Soc Trang and Tien
Giang with over 3,000 cases of dengue. The incident of morbidity and

mortality from dengue in the period of 2004-2008 in the Southern coastal
plain showed no positive signs. The incidence of morbidity and mortality is
still high. In 2007, the ratio of morbidity/100,000 population of the whole
region was 395/100,000 people, calculated from 1998 (the period of starting
the National Dengue Fever Prevention Target Program), this was the year
with ratio/100,000 people was quite high. In 2011, the total number of
dengue cases was reported as 20,459 cases, an average of 414 cases/week.
Since August 2012, the number of cases has decreased steadily in the
following months and lower than the warning threshold.
3.2.2. Correlation between climate and dengue in the southern coastal
region
* Pearson’s r correlation analysis:
Table 3.1. Correlation between cases of dengue and climate features
Correlation coefficients
r
p
Temperature
0.063
0.471
Humidity
0.491
0.001
Rainfall
0.644
0.001
There was a strong correlation between average rainfall and average number
of cases in the period of 2003-2013 (Pearson’s r = 0.644).
In months of high temperature, the number of dengue cases decreased and
vice versa. The average number of cases in 2003-2013 was inversely
proportional to the average temperature in this period. However, the

correlation between temperature and number of cases was weak (Pearson’s r
= 0.063).
In the months of high humidity, the number of cases with dengue increased
and vice versa. The average number of cases in 2003-2013 was directly
proportional to the average humidity in this period. However, the correlation
between humidity and number of cases was moderate (Pearson’s r = 0.491).


15

Figure 3.5. Cross correlation between dengue cases and rainfall in the
period of 2003-2013
There was a clear correlation between rainfall and dengue cases, the peaks of
rainfall also corresponded to the peak of cases. Cross-correlation between
the number of cases of dengue and high precipitation, was directly
proportional to lag 1-2 accumulated rainfall (lag = -1, -2) and at the time (lag
= 0). The highest correlation coefficient with the latency of 0 (lag = 0).

Figure 3.6. Cross correlation between dengue cases and humidity in the
period of 2003-2013
In the years, the peak of the epidemic always coincides with the peak of the
year. The number of cases of dengue was highly correlated, directly
proportional to lag 1-relative humidity (lag = -1), at time (lag = 0) and after 1
month (lag = 1).


16

Figure 3.7. Cross correlation between dengue cases and temperature in the
period of 2003-2013

There is a clear correlation between temperature and number of cases with of
dengue. Dengue incidents were found to correlate proportionally with lags 13 high temperature (lag = -3, -2, -1), and highest at lag-3 temperature (lag =
-3).
3.2.3. Correlation between climate and vector of dengue in Kien Giang
in the period of 2011–2013
3.2.3.1. Correlation between climate and vector of dengue in Kien Giang
in the period of 2011–2013:
Table 3.2. Correlation between rainfall and insect indices, 2011-2013
Larvae Index
Density Index
Average rainfall
Month
DI (Number of
HI
CI
(mm)
BI
mosquitoes/house)
(%)
(%)
0.32
44.40
26.17
13.48
1
15.38
0.28
41.09
26.15
13.74

2
5.57
0.40
46.66
26.88
13.66
3
64.19
0.46
57.29
38.17
20.57
4
86.52
0.47
61.07
32.77
21.06
5
226.71
0.51
58.69
35.54
18.98
6
236.90
0.69
57.29
30.25
15.74

7
231.57
0.54
60.49
34.24
17.11
8
214.57
0.48
57.76
35.30
16.15
9
347.29


17

Average rainfall
Month
(mm)

Density Index
DI (Number of
mosquitoes/house)

Larvae Index
HI
CI
BI

(%)
(%)

0.42
53.75
31.35
14.96
10
209.48
0.45
53.60
32.42
14.49
11
134.67
0.57
46.14
31.43
13.37
12
25.29
0.287
0.516
0.401
0.254
Correlation coefficient r
< 0.001
< 0.05
> 0.05
> 0.05

p
In the rainy season with rainfall of 200 mm and above, density index of
mosquitoes also increased and the month of high risk of incident was July
(DI = 0.69). The correlation between rainfall and BI and HI is average
correlation (Pearson’s r>0.3). April is the month that mosquitoes most
produce eggs, therefore HI is usually the highest in this month (38.17%) and
decreases gradually at the end of the year. The correlation between rainfall
and DI and CI is a low correlation (Pearson’s r ≤ 0.3).
Table 3.3. Correlation between temperature and insect indices, 2011-2013
Density Index
Larvae Index
Average
Month
DI (Number of
temperature
BI
HI CI (%)
mosquitoes/house)
1
25.91
0.32
44.40 26.17 13.48
2
26.54
0.28
41.09 26.15 13.74
3
27.71
0.40
46.66 26.88 13.66

4
28.39
0.46
57.29 38.17 20.57
5
28.52
0.47
61.07 32.77 21.06
6
27.92
0.51
58.69 35.54 18.98
7
27.44
0,69
57.29 30.25 15.74
8
27.66
0.54
60.49 34.24 17.11
9
26.93
0.48
57.76 35.30 16.15
10
27.48
0.42
53.75 31.35 14.96
11
27.41

0.45
53.60 32.42 14.49
12
26.33
0.57
46.14 31.43 13.37
Correlation coefficient r
0.081
0.402 0.403 0.302
< 0.05
< 0.05 > 0.05
p
> 0.05


18

There was a significant correlation between the average temperature in the
period of 2011-2013 with the insect indices, especially the average
correlation between temperature and HI index and BI index (0.3 <0 , 7). The mosquito density index in Kien Giang during the middle of rainy
season (from June to August) was always greater than 0.5. Correlation
between temperature and CI index was a moderate correlation (0.3
Table 3.4. Correlation between average humidity
period of 2011-2013
Density Index
Average
Month
DI (Number of

temperature
mosquitoes/house)
1
78.67
0.32
2
77.38
0.28
3
77.95
0.40
4
79.29
0.46
5
83.67
0.47
6
84.52
0.51
7
84.90
0.69
8
84.62
0.54
9
86.62
0.48
10

83.86
0.42
11
83.43
0.45
12
80.33
0.57
Correlation coefficient r
0.374
p
< 0.05

and insect indices in the
Larvae Index
BI

HI

CI (%)

44.40
41.09
46.66
57.29
61.07
58.69
57.29
60.49
57.76

53.75
53.60
46.14
0.558

26.17
26.15
26.88
38.17
32.77
35.54
30.25
34.24
35.30
31.35
32.42
31.43
0.400

13.48
13.74
13.66
2.57
21.06
18.98
15.74
17.11
16.15
14.96
14.49

13.37
0.173

< 0.001

< 0.05

> 0.05

There was a relatively high correlation between the average humidity in the
period of 2011 - 2013 with insect indexes, especially with BI and HI. Months
with an average humidity of over 80%, also saw an increase in DI and BI
indicators. The correlation between average moisture content and mosquito
density index also reached moderate level with r = 0.374.


19

3.3. EVALUATION OF EFFECTIVENESS OF ABATE 1SG AGAINST
AEDES LARVAE
3.3.1. General assessment before and after application:
Table 3.5: Comparison results before and after application:
Intervention group (n =
Control group (n = 345)
348)
Evaluating
Comparison before
time
CI
CI (+)

and after
EI(%)
± SD EI (%)
(+)
%
application
Before
83.3
38.21 ±
application
68.997
After 24
0.0
0
100
84.9
31.35 ± 42.41
hours
After 1
0
0
100
79.4
44.43 ± 57.68
6.48
month
After 3
1.1 0.03 ± 0.32 98.68 72.5
37.23 ± 50.06
14.61

months
Assessing EI in the intervention group, it reached 100% after 24 hours. It
maintained 100% after a month; and after 3 months, EI was staying around
98.68%. In the control group, despite an addition of the campaign of
environmental sanitation against larvae, the EI was only 6.48% after a month
and 14.61% after 3 months.
3.3.2. Evaluate the effectiveness of larval killing via other indicators
Table 3.6. Change in house index with larvae (HI):
HI
Intervention group Control group
Before application
83.49
86.89

Comparison
p=0.339

After 24 hours

0

86.89

p=0.0001

After 1 month

0

71.84

p=0.0001

After 3 months

1.89

60.68

p=0.0001

Before application, comparing HI between two groups, there was no
difference between the intervention group and the control group (p > 0.05).


20

However, after application, HI showed a marked difference between the two
groups and it showed statistical significance (p < 0.01).
Table 3.7. Changes in Breteau index (BI):
BI
Intervention group Control group Comparison
Before application 136.79
142.23
p=0.532
After 24 hours

0

142.23

p=0.0001

After 1 month
After 3 months

0
1.89

133.01
121.36

p=0.0001
p=0.0001

The evaluation by BI index in the above table showed that there was a
difference between the intervention group and the control group in all the
surveyed periods and this difference is statistically significant (p <0.05).
CHAPTER 4
DISCUSSION
4.1 Climate features of southern coastal region in the period of 20032013:
The study showed that the temperature in the region for 11 years was 2627°C, with a temperature variation of 3-3.5°C, with a clear seasonal and
annual cycle.
The annual humidity was over 70%, almost 75% (in 11 years, only 3 months
with the moisture content below 75%). It tended to increase steadily
throughout the year, peaking from July to October; the lowest was in in April
corresponding to the month with the highest temperature in the year. The
annual average humidity is 81.87%. Moisture conversion cycle became
different with a period of 5 to 6 months.
Rainfall in the year is divided into 2 distinct seasons, about half a year of

rainfall in the month is less than 200mm and half a year of rainfall in the
month is over 200mm with a 6 month cycle. High rainfall concentrates in
June to October of the year.
4.2. The correlation between climate and dengue in the southern coastal
region:
According to the research, it is said that the number of cases of dengue is
strongly correlated with the cyclical nature of climate factors. Thereby the
number of cases is strongly correlated with temperature and humidity,


21

especially with lag-3 temperature and lag1–relative humidity. The above
results are completely consistent with the study of Le Thi Ngoc Anh et al.,
which has shown that the correlation latency from 1 with R2 is 0.52 and
0.73. Respectively, the result is also the same as that of the study by Nguyen
Phuong Toai et.al, pointing out that the results of the autocorrelation analysis
of new cases showed the greatest correlation at the 1-month latency.The
latency factor shows that outbreaks can be a consequence of the earlier stage
of insect and pathogen development. The late effects of climate on the
incidence of dengue may be explained by climate variables that do not
directly affect the new incidence but only indirectly affect the epidemic
process.
The results of our study are consistent with the study of Ivrahima Diouf in
Senegal with the results demonstrated that the rate of Dengue infection is
strongly correlated with climate factors, especially rainfall. Along with that
is the study of the correlation between dengue and rainfall and moisture
content (RR = 1.06 and RR = 1.05 in the multivariate Poisson regression
model) in some northern coastal locations in Vietnam in 2014. However, in
this study, the temperature did not show a high correlation with the disease.

Our results are also consistent with Liang Lu's study. Wind speed is inversely
correlated with prevalence of dengue in the same month. This effect may be
due to reduced mosquito density due to higher wind speeds. A negative
correlation was found between wind velocity and mosquito density. Wind
tends to stop mosquitoes from flying and therefore may have affected their
nourishment.
The results of our research on disease characteristics are consistent with the
study of Pham Thi Nha Truc (2014) on dengue in Gia Rai district, Bac Lieu
province (also a province in the Mekong Delta) from 2006–2012. This
proves that dengue has a distinct seasonal nature, the disease increases in
June to November every year, the highest in July, August and September.
Dengue outbreaks have occurred regularly every 3–4 years.
Our study of humidity has a strong correlation with dengue. This is also
consistent with the study of Suchithra Naish (2014). The study shows that
dengue epidemic correlates with the period of high humidity in the year. In
the study, the effects of weather variables and the incidence of dengue
showed that the geographical limit in the spread of dengue was strongly


22

influenced by the weather factor including moisture. Moisture is an
important factor dominated by temperature and rainfall. High humidity
occurs when both temperature and rainfall are high.
4.3. Effectiveness of ABATE 1SG against Aedes larvae
In An Hoa ward, we also surveyed 212 households with 348 water storage
containers, recording all water storage containers and the presence of larvae,
finding and marking water storage containers that could be applied with
ABATE 1SG, especially water storage containers that it would be difficult to
eliminate larvae by conventional ways without ABATE 1SG application.

ABATE 1SG must not be applied for water storage containers for eating or
drinking or are the habitat of fish or other natural enemies. In addition, to
ensure absolute safety during the testing process, we also excluded
ornamental plants with high economic value.
In An Binh, after investigating 206 households in the control group we
recorded received 345 water containers, all of which were marked for
monitoring.
Before application, we conducted the evaluation of larvae indicators in both
the intervention and control groups and all recorded the abundance of larvae
in some water storage containers. In the trial area, after the survey, all water
storage containers eligible for study were marked and treated with 1%
ABATE 1SG at 1g/10 liter of water. In the control group, water storage
containers that could be applied with ABATE 1SG (also eligible for study)
were selected and marked but not released ABATE 1SG.
Results in the trial area before ABATE 1SG application: the CI was 83.3%.
After ABATE 1SG application: after 24 hours of re-evaluation, we found that
in the group no water storage containers had larvae. In the control area,
before the trial, the CI was 84.9%.
One month after applying ABATE 1SG, after re-evaluating the status of
larvae in water storage containers, we found that in the group no water
storage containers had larvae while the control group had the CI of 79.4%.
After 3 months, we found that the CI was 1.1%. while the control group had
CI ratio of 72.5%. Observing the larvae in water storage containers in the
test group, we found that some of them had a change in water volume, in
particular, it increased more than before, some had sand fell down and this
may have buried the ABATE 1SG particles that did not work. The


23

effectiveness of larvae removal in the intervention group reached 100% in
the first 24 hours and remained 98.68% effective after 3 months.
The evaluation of other larvae indicators also showed similar results, House
index (HI) in the intervention group decreased from 83.49% to 0% in the
first 24 hours, after 3 months this index was 1.89%; in the control group, HI
was from 86.89% before the test and was 60.68% after 3 months. Breteau
index (BI) in the experimental group from 136.79 before the trial, after only
3 months, it was only 1.89. In the control group before the trial, BI was
142.23; after 3 months is 121.36.
Thus, the results of field testing in a residential cluster also show that
ABATE 1SG has a significant effect of killing larvae, especially water
storage containers that cannot eliminate larvae by conventional methods in
environmental sanitation campaigns against dengue fever. ABATE 1SG kills
100% of larvae in the first month and the killing effect still last at least 3
months later. Especially in case of water storage containers in residential
clusters, mainly are left outside and there is no lid, the amount of water
always changes but the effectiveness of ABATE 1SG still remains great.
CONCLUSION
1. Climate features of southern coastal region in the period of 20032013
The climate factors in the southern coastal region in 11 years of study
evolved according to a clear cycle of months and years. There was no
obvious change in temperature, humidity and rainfall during the surveyed
period. Climate variables are characterized by a hot and humid climate with
two distinct seasons: rainy and dry one.
2. The correlation between climate features and dengue in the
southern coastal region
Dengue appeared all year round with the lowest frequency in February,
March and April, starting to increase from May, gradually increasing in June
and peaking in rainy months: July, August, September, October. In 11 years
of study, there were 3 peaks of outbreaks in 2004, 2008, 2011, the outbreak

period of dengue was 3 to 4 years.
The number of cases dengue has a clear correlation with the climatic
variables. The number of dengue cases is closely correlated with